Measured evidence · DS-STABLE-STATE-SELECTION

Selection of profiled stable states was measured

Measuredindependently auditedpublication: internalno direct precedent found

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Meaning

Experiments find both margin regimes and examine which states ascent selects at increasing sample sizes.

Statement

Exact full-lattice census (N = 10..14, K = 3, centered06 + mix3 grid laws) finds one-point exchange-stable profiled-Ds states plentiful (5-944 per instance, correcting the pre-audit 18-944 range) and overwhelmingly non-global. On the centered law their nuisance blocks span 1e-5 to 0.57 with value gap and nuisance block anti-correlated (-0.27 to -0.83 per instance); margin-retaining non-global stable states occur in every census instance at a Theta(1) price, and near-coincident projected centroids occur, so (M5) must be checked. The efficient-score DP interval labeling is unstable in 7/10 centered instances (already N = 8, exact gain 0.447) and stable in 9/10 mix3 instances. Small-N ascent is seed-dependent. In the researcher library runs at N = 100/300/1000 every tested seed on the centered law terminates with nuisance at K/N scale and near-optimal value; 0.004-0.046 is an aggregate reported gap summary, not a run-wise bound. An independent N = 100 run reproduced stability and collapse for all three seeds but observed a random-seed gap 0.075. On mix3 the independent runs retained lambda_min about 1.7 with gaps below 7e-5. These are measured observations, not an asymptotic selection theorem.

Assumptions

  • grid-law emulations (atomic), deterministic researcher seeds 20260830 + 1000N + rep; independent audit seeds and exact provenance are in AUDITS/artifacts/AUDIT-DS-STABLE-MARGINS-COMPILE-001

  • measured, never theorem authority; the asymptotic selection law is open (OPEN-DS-STABLE-BASINS)

the selection-effects evidence separating properties of stable states from properties of the seeding (study blocker 5)

Where it stops

Audit-hardened measured claim. The stable-count range is 5-944. The 0.004-0.046 researcher gap range is aggregate, not a universal per-run range; an independent N=100 random seed produced 0.075. Atomic grid laws and finite optimizer runs do not prove asymptotic basin selection.

Refuted by

  • Counterexample fixtureCE-DS-INTERVAL-SEED-UNSTABLE-001

    The exact efficient-score interval labeling - the DP optimum of the full-sample efficient score, the documented initializer for profiled exchange and the finite analogue of the DS15 degenerate attainer J* - is itself one-point exchange-stable for the in-bin profiled-Ds objective. FALSE: on this exactly centered N=8 sample from the centered06 grid law, relocating row 7 to cell 1 raises the profiled value by 0.447 exactly. The improving move works by growing the binned nuisance block 27-fold (0.0042 -> 0.111): near the interval seed the projection tax is the dominant term and the profiled objective climbs by buying back nuisance information, the finite mechanism behind DS15 Proposition 6's steering.

Closest prior work

Relationships

Rests on

The full chain beneath it

Enables

Raises

Open next door

Local graph
Local map of Exchange-stable Ds states span both margin regimes; ascent selects the funnel at scale3 prerequisites to the left, 2 results it enables or questions it raises to the right, 1 boundary cases below.Monotone exact Ds exchange terminates finitelyMonotone exact Ds exc…Exact profiled leverage stability boundExact profiled levera…Margin price and value funnel at arbitrary finite Ds labelingsMargin price and valu…Profiled compile verdict is selected by an observable certificate stateProfiled compile verd…Wasted-cell tracking and constrained-value attainmentWasted-cell tracking…Exchange-stable Ds states span both margin regimes; ascent selects the funnel at scaleExchange-stable Ds st…CE-DS-INTERVAL-SEED-UNSTABLE-001CE-DS-INTERVAL-SEED-U…
Prerequisites to the left, what it enables or raises to the right, boundary cases below. Open in the map.

Proof

DS16. Margin price at arbitrary labelings, the value funnel, and the profiled compile verdict

Audit (30 Aug 2026, AUDITS/AUDIT-DS-STABLE-MARGINS-COMPILE-001.md): all three claims are hardened. The PRICE/FUNNEL/FLOOR theorem is verified after replacing a pointwise SLLN at a data-dependent centroid limit by a uniform strong law on compact tilt--codebook sets, making the all-labelings event explicit, and fixing the raw-label/exact-centering convention in the FLOOR. The compile claim now says only currently established in the registered theory, not mathematical uniqueness: DS14 is a theorem for certified sequences, and a single finite certificate supplies diagnostics but no population guarantee. The measured census range is corrected from 18--944 to 5--944, and its reported library gap interval is identified as an aggregate summary rather than a run-wise bound.

Setting: exactly DS15's — S=(Sψ,Sλ)∼PS=(S_\psi,S_\lambda)\sim P on R2\mathbb R^2, ES=0ES=0, E∥S∥2<∞E\|S\|^2<\infty, I≻0I\succ0, class (L) (conditional centering) + (S) (scalar regularity of law⁡(s^)\operatorname{law}(\hat s)); (R) is not needed here except where DS15's conclusion (1) is imported for a comparison. Equal weights, centered score rows S~i=Si−SˉN\tilde S_i=S_i-\bar S_N in every empirical information calculation, K≥3K\ge3 (=dψ+dλ+1=d_\psi+d_\lambda+1; see the cardinality restatement below), feasible labelings = nonsingular binned nuisance block I^λλ>0\hat I_{\lambda\lambda}>0. vKv_K, J∗J^*, wb∗w^*_b, v^K\hat v_K, btw(s^N;z)\mathrm{btw}(\hat s_N;z) as in DS15.

Cardinality, restated (library commit 891bbf3, 30 Aug 2026). The registered condition K≥dλ+2K\ge d_\lambda+2 is a dψ=1d_\psi=1 coincidence. The mechanism is ∑bmb=μ^\sum_b m_b=\hat\mu (with mb=∑i∈bwisim_b=\sum_{i\in b}w_is_i): the binned moment vectors of an exactly centered sample satisfy one linear relation, so rank⁡(Iz)≤K−1\operatorname{rank}(I_z)\le K-1, and a nonvacuous profiled value needs K−1≥d=dψ+dλK-1\ge d=d_\psi+d_\lambda, i.e. K≥dψ+dλ+1K\ge d_\psi+d_\lambda+1 on a centered sample. At dψ=1d_\psi=1 this is exactly K≥dλ+2K\ge d_\lambda+2, which is why CE-DS-MARGINS-RANK-VACUITY-001 (a dψ=1d_\psi=1 witness) suggested the narrower formula; its consequences[0] line carries that dψ=1d_\psi=1 restriction implicitly.

The algebraic rank bound can be one larger for a matrix built from rows with nonzero empirical mean. That is not an alternative Fisher-score regime: scores have mean zero, and ScoreQuant's empirical information uses exact centering. No off-centered compile claim is inferred from that matrix fact.

The question

DS15 shows free global finite DsD_s optima converge to the nuisance-degenerate efficient-score interval quantizer: (M2) holds, (M3) fails. The library's optimizer returns one-point exchange-stable, generally non-global states (DS-EXCHANGE-TERMINATES), and DS15 asserts nothing about them. OPEN-DS-MARGINS-NONCENTERED's deployment half asks: do those states retain the DS14 margins, at what information cost vK−Φ^sv_K-\hat\Phi_s, and does a theorem-backed inductive compile rule for profiled criteria exist beyond the projected efficient-score interval rule?

The first observation is that the question is not a universal quantification: global optima are themselves exchange-stable, so DS15 already exhibits stable sequences along which (M3) fails. What decides the compile question is (i) whether the margins are priced — whether any labeling carrying them must sit a definite distance below the supremum — and (ii) which regime the optimizer's terminal states actually occupy.

Theorem (margin price and the value funnel)

Under (L)+(S), dψ=dλ=1d_\psi=d_\lambda=1, K≥3K\ge3, equal weights, almost surely:

  1. (Price.) For every κ>0\kappa>0 there is δ(κ)>0\delta(\kappa)>0, depending only on (P,K,κ)(P,K,\kappa), with lim sup⁡N  sup⁡{Φ^s(z)  :  z feasible, I^λλ(z)≥κ}  ≤  lim sup⁡N  sup⁡{btw(s^N;z)  :  I^λλ(z)≥κ}  ≤  vK−δ(κ).\limsup_N\; \sup\bigl\{\hat\Phi_s(z)\;:\;z\ \text{feasible},\ \hat I_{\lambda\lambda}(z)\ge\kappa\bigr\} \;\le\; \limsup_N\; \sup\bigl\{\mathrm{btw}(\hat s_N;z)\;:\; \hat I_{\lambda\lambda}(z)\ge\kappa\bigr\} \;\le\; v_K-\delta(\kappa). Since λmin⁡(I^N)≤I^λλ\lambda_{\min}(\hat I_N)\le\hat I_{\lambda\lambda}, the same cap holds under the DS14 conditioning margin (M3) at level κ\kappa. The hypothesis is a margin, not stability or optimality: every margin-carrying labeling — exchange-stable or not, optimizer-produced or not — pays at least δ(κ)\delta(\kappa) of profiled information relative to the unrestricted supremum vKv_K that free global optima attain under (L)+(S)+(R) (DS15 conclusion 1).
  2. (Funnel.) Any sequence of feasible labelings with Φ^s(z(N))→vK\hat\Phi_s(z^{(N)})\to v_K — in particular any asymptotically value-optimal solver output, from any seed, stable or not, global or not — satisfies: cells converge in sample measure to J∗J^*, min cell mass →min⁡bwb∗>0\to\min_b w^*_b>0 ((M2) holds; singletons die out), I^λλ,I^ψλ→0\hat I_{\lambda\lambda},\hat I_{\psi\lambda}\to0, hence λmin⁡(I^N)→0\lambda_{\min}(\hat I_N)\to0 ((M3) fails), and the (M5) object B^z=I^ψλ/I^λλ\hat B_z=\hat I_{\psi\lambda}/\hat I_{\lambda\lambda} rides the same 0/00/0 as in DS15. DS15's conclusions (2)–(3) are therefore value-topological, not properties of exact global optimality.
  3. (Floor.) For every fixed measurable KK-cell quantizer qq on the raw score SS, with Wb>0W_b>0 and Iq,λλ>κI_{q,\lambda\lambda}>\kappa, label row ii by q(Si)q(S_i) and compute its empirical information from the centered rows S~i\tilde S_i. Those labelings are eventually feasible with I^λλ≥κ\hat I_{\lambda\lambda}\ge\kappa and Φ^s→Φ(q)\hat\Phi_s\to\Phi(q). Hence the supremum in (1) is asymptotically at least v∗+(κ):=sup⁡{Φ(q):Iq,λλ>κ}v^{*+}(\kappa):=\sup\{\Phi(q):I_{q,\lambda\lambda}>\kappa\}, and v∗+(κ)≤vK−δ(κ)v^{*+}(\kappa)\le v_K-\delta(\kappa); DS15's margin-compatible optimum v∗(κ)v^*(\kappa) (over λmin⁡(Iq)≥κ\lambda_{\min}(I_q)\ge\kappa, a subclass) obeys v∗(κ)≤v∗+(κ)v^*(\kappa)\le v^{*+}(\kappa). This is a supremal lower bound: it asserts neither attainment nor one-sided continuity of either constrained value in κ\kappa.

Proof

Throughout, work on one probability-one event where: v^K(s^N)→vK\hat v_K(\hat s_N)\to v_K and the tilt-Lipschitz bound of DS15 Proposition 5 holds (its proof needs only (M1)-type moments and (S); the same argument gives v^K−1→vK−1\hat v_{K-1}\to v_{K-1}); B^N∗→B∗\hat B^*_N\to B^* and the SLLN holds for ∥S∥2\|S\|^2, Sλ2S_\lambda^2, and the fixed cells 1Jb∗1_{J^*_b} weighted by SλS_\lambda; the Glivenko–Cantelli law holds over the fixed VC class of tilted half-planes {s:sψ−βsλ≤c}\{s:s_\psi-\beta s_\lambda\le c\}, (β,c)(\beta,c) in a compact neighborhood of (B∗,⋅)(B^*,\cdot), both unweighted and with integrable envelope ∣Sλ∣|S_\lambda|. For the signed weight, apply the VC theorem to Sλ+1HS_\lambda^+1_H and Sλ−1HS_\lambda^-1_H separately; compact tilt control is already included because all (β,c)(\beta,c) half-planes form one fixed finite-VC class, and E∣Sλ∣<∞E|S_\lambda|<\infty follows from the second moment. Also include the uniform strong law

sup⁡β∈B, C∈[−R,R]K∣(PN−P)min⁡c∈C(Sψ−βSλ−c)2∣→0 \sup_{\beta\in\mathcal B,\ C\in[-R,R]^K} \left|(P_N-P)\min_{c\in C}(S_\psi-\beta S_\lambda-c)^2\right|\to0

for every compact B\mathcal B containing B∗B^* and finite RR. This follows by truncation and finite parameter nets: the class is continuous in the finite-dimensional parameter (β,C)(\beta,C), and on each compact set has an integrable envelope AR(1+∥S∥2)A_R(1+\|S\|^2). Finally include the empirical DP boundaries and masses of J^N∗\hat J^*_N converge to J∗J^*'s (the audit-hardened boundary/mass consistency ingredient of DS15 Proposition 6, which needs only (S)).

Lemma DS16.1 (empirical grouping rigidity, uniform). For every ε>0\varepsilon>0 there are δ0>0\delta_0>0 and an a.s. finite N0N_0 such that for all N≥N0N\ge N_0 and every KK-grouping zz of the sample indices with btw(s^N;z)≥v^K−δ0\mathrm{btw}(\hat s_N;z)\ge \hat v_K-\delta_0: after relabeling, P^N(z-cellb Δ {s^N∈Jb∗})≤ε\hat P_N(z\text{-cell}_b\,\Delta\,\{\hat s_N\in J^*_b\})\le\varepsilon for every bb, and W^b(z)≥wb∗−2ε\hat W_b(z)\ge w^*_b-2\varepsilon.

Proof. This is DS15 Lemma 3's five-step architecture run on the empirical scalar sample, with groupings in place of measurable partitions — the one genuine gap between the two settings, closed as follows. Write xi=s^N,ix_i=\hat s_{N,i}, P^Ns^2=btw(z)+WSSE(z)\hat P_N\hat s^2=\mathrm{btw}(z)+\mathrm{WSSE}(z), so the hypothesis reads WSSE(z)≤W^K+δ0\mathrm{WSSE}(z)\le\hat W_K+\delta_0 with W^K=P^Ns^2−v^K\hat W_K=\hat P_N\hat s^2-\hat v_K the optimal empirical KK-grouping SSE (attained by sorted intervals — the 1-D contiguity fact of DS15 Proposition 4, verified on the full lattice in the identity suites).

(i) Inactive-cell budget. For η>0\eta>0 call bb active when W^b≥η\hat W_b\ge\eta. Uniform integrability transfers: for any TT, sup⁡P^N(B)≤mP^N[s^21B]≤2(P^N[sψ21sψ2>T]+B^N∗2P^N[sλ21sλ2>T])+2(1+B∗2)Tm+o(1)\sup_{\hat P_N(B)\le m}\hat P_N[\hat s^21_B]\le 2\bigl(\hat P_N[s_\psi^21_{s_\psi^2>T}]+\hat B_N^{*2}\hat P_N[s_\lambda^21_{s_\lambda^2>T}]\bigr)+2(1+B^{*2})Tm+o(1), and the tail terms converge to their population values by the SLLN on fixed functions; so inactive cells contribute τ(Kη)+o(1)\tau(K\eta)+o(1) to the between value with τ(m)↓0\tau(m)\downarrow0.

(ii) Deletion comparison and (iii) full support. If one cell has mass below η\eta, merge it into a bounded active cell. The increment in SSE is bounded by the inactive cell's second-moment contribution plus its mass times an active-centroid bound, hence by ρ(η)+o(1)\rho(\eta)+o(1), where ρ(η)↓0\rho(\eta)\downarrow0 by (i). The resulting grouping uses at most K−1K-1 cells, so its SSE is at least W^K−1\hat W_{K-1}. Therefore W^K−1−W^K≤δ0+ρ(η)+o(1)\hat W_{K-1}-\hat W_K\le\delta_0+\rho(\eta)+o(1). But W^K−1−W^K→WK−1−WK>0\hat W_{K-1}-\hat W_K\to W_{K-1}-W_K>0 (value convergence at both budgets; strict positivity from (S), whose positive density near the optimal boundaries in particular rules out a finite-support collapse). Choose η\eta, then δ0\delta_0, below this gap: every cell is active. This also closes the apparent KK-versus-K−1K-1 loophole; an empty cell is simply the η=0\eta=0 case.

(iv) Centroid convergence, uniform over groupings. This is the standard almost-minimizer rigidity principle for k-means codebooks (Rakhlin--Caponnetto 2006 supplies direct bounded-source prior art), with the grouping-to-nearest-center reduction made explicit here. Suppose groupings z(Nj)z^{(N_j)} with WSSE≤W^K+δj\mathrm{WSSE}\le\hat W_K+\delta_j, δj→0\delta_j\to0, had active-centroid sets escaping a neighborhood of C∗C^*. Active centroids are bounded (moment bound), so a subsequential limit set C′≠C∗C'\ne C^* exists. The nearest-point SSE is grouping-independent: SSEP^N(c(z))≤WSSE(z)\mathrm{SSE}_{\hat P_N}(c(z))\le\mathrm{WSSE}(z): reassigning every observation to a nearest centroid cannot increase SSE, even when duplicate atoms were split among cells. By the compact-set uniform law displayed above, simultaneously for the data-dependent B^N∗\hat B_N^* and all bounded codebooks, SSEP(c(z(Nj)))≤W^K+δj+o(1).\mathrm{SSE}_{P}(c(z^{(N_j)})) \le \hat W_K+\delta_j+o(1). Continuity in the codebook then gives SSEP(C′)≤WK\mathrm{SSE}_P(C')\le W_K, contradicting (S)-uniqueness when C′≠C∗C'\ne C^*. This uniform law is essential: a pointwise SLLN for the random subsequential limit C′C' would be invalid. Thus near-optimal groupings have centroid sets uniformly convergent to C∗C^*.

(v) Misassignment slabs. For a grouping zz with centroids γ\gamma-close to C∗C^*: a point on cell aa's side at distance ≥t\ge t from the midpoint of (ca,cb)(c_a,c_b) but assigned to bb pays excess (x−cb)2−(x−ca)2≥2t g/2(x-c_b)^2-(x-c_a)^2\ge 2t\,g/2 with g=g= the minimal C∗C^* centroid gap, once γ<g/4\gamma<g/4; so the P^N\hat P_N-mass misassigned beyond the tt-slabs is ≤(δ0+o(1))/(tg/2)\le(\delta_0+o(1))/(tg/2), while the slabs themselves lie inside fixed (t+γ)(t+\gamma)-slabs around the C∗C^* midpoints whose empirical mass converges to the population slab mass, small by (S)-atomlessness. Choosing tt then δ0\delta_0 gives the symmetric difference bound against the empirical Voronoi cells of C∗C^*; replacing them by J^N∗\hat J^*_N's cells (boundary/mass consistency) and by the fixed sets {s^N∈Jb∗}\{\hat s_N\in J^*_b\} costs empirical slab masses that vanish by the same GC-plus-atomlessness argument. Masses follow: W^b≥P^N(s^N∈Jb∗)−ε→wb∗−ε\hat W_b\ge \hat P_N(\hat s_N\in J^*_b)-\varepsilon\to w^*_b-\varepsilon. ∎

Proof of (1). Define a supremum over an empty feasible set as −∞-\infty. For each NN, both suprema are maxima of finitely many extended-real measurable functions of the sample, so they are measurable. Intersecting the probability-one uniform-law events above over integer compact radii and rational tolerances produces one measurable event on which the argument is pathwise and simultaneous over all labelings at every NN. Consequently the conclusion holds for every labeling sequence selected on that event, including a data-dependent selection; no separate exceptional set is chosen per sequence. When the constrained set is nonempty, let z(N)z^{(N)} attain the btw\mathrm{btw}-maximum subject to I^λλ≥κ\hat I_{\lambda\lambda}\ge\kappa. The first inequality is DS15 Proposition 4 (exact, every sample, every feasible labeling). Fix κ\kappa; suppose along a subsequence btw(s^N;z(N))>vK−δ\mathrm{btw}(\hat s_N;z^{(N)})> v_K-\delta. Since v^K→vK\hat v_K\to v_K, for large NN the hypothesis of Lemma DS16.1 holds with δ0=2δ\delta_0=2\delta. Take ε=ε(κ)\varepsilon=\varepsilon(\kappa) to be fixed below and δ=δ0(ε)/2\delta=\delta_0(\varepsilon)/2. The lemma gives, per cell,

∣m^λ,b(z(N))−P^N[Sλ1s^N∈Jb∗]∣≤(P^NSλ2)1/2ε1/2\bigl|\hat m_{\lambda,b}(z^{(N)})-\hat P_N[S_\lambda1_{\hat s_N\in J^*_b}] \bigr| \le\bigl(\hat P_NS_\lambda^2\bigr)^{1/2}\varepsilon^{1/2}

(Cauchy–Schwarz over the symmetric difference), while P^N[Sλ1s^N∈Jb∗]→E[Sλ1s^∈Jb∗]=0\hat P_N[S_\lambda1_{\hat s_N\in J^*_b}]\to E[S_\lambda1_{\hat s\in J^*_b}]=0 — the weighted GC law over the tilted half-plane class absorbs B^N∗→B∗\hat B^*_N\to B^*, dominated convergence plus (S)-atomless boundaries give continuity in the tilt, and (L) makes the limit zero. With W^b≥wb∗−2ε≥wmin⁡∗/2\hat W_b\ge w^*_b-2\varepsilon\ge w^*_{\min}/2 for ε\varepsilon small,

I^λλ(z(N))=∑bm^λ,b2W^b≤2Kwmin⁡∗(Cε1/2+o(1))2,\hat I_{\lambda\lambda}(z^{(N)}) =\sum_b\frac{\hat m_{\lambda,b}^2}{\hat W_b} \le\frac{2K}{w^*_{\min}}\bigl(C\varepsilon^{1/2}+o(1)\bigr)^2,

with C2=2ESλ2C^2=2ES_\lambda^2, say. Choose ε(κ)\varepsilon(\kappa) so the right side is eventually <κ<\kappa: contradiction with I^λλ≥κ\hat I_{\lambda\lambda}\ge\kappa. Hence lim sup⁡sup⁡{btw}≤vK−δ(κ)\limsup\sup\{\mathrm{btw}\}\le v_K-\delta(\kappa) with δ(κ)=δ0(ε(κ))/2\delta(\kappa)=\delta_0(\varepsilon(\kappa))/2. The (M3) transfer is the diagonal bound λmin⁡(I^N)≤eλ⊤I^Neλ=I^λλ\lambda_{\min}(\hat I_N)\le e_\lambda^\top\hat I_Ne_\lambda =\hat I_{\lambda\lambda}. ∎

Proof of (2). Φ^s(z(N))→vK\hat\Phi_s(z^{(N)})\to v_K forces btw(s^N;z(N))→vK\mathrm{btw}(\hat s_N;z^{(N)})\to v_K (Proposition 4 sandwich with v^K→vK\hat v_K\to v_K). Apply Lemma DS16.1 with εm↓0\varepsilon_m\downarrow0 along δm↓0\delta_m\downarrow0 and diagonalize: symmetric differences to J∗J^*-cells vanish, so masses converge to wb∗w^*_b (min mass positive, singletons die), and the Step-3 display above with ε→0\varepsilon\to0 gives m^λ,b→0\hat m_{\lambda,b}\to0, hence I^λλ→0\hat I_{\lambda\lambda}\to0; the cross block I^ψλ=∑bm^ψ,bm^λ,b/W^b→0\hat I_{\psi\lambda}=\sum_b\hat m_{\psi,b}\hat m_{\lambda,b}/\hat W_b\to0 since m^ψ,b\hat m_{\psi,b} is bounded and masses are bounded below; λmin⁡≤I^λλ→0\lambda_{\min}\le\hat I_{\lambda\lambda}\to0. ∎

Proof of (3). For a fixed qq, label by q(Si)q(S_i), not by applying an arbitrary discontinuous rule to the sample-centered row. Masses and raw moments are sample means of fixed integrable functions. Exact centering only changes the empirical cell moment by

m^b=PN[S1{q(S)=b}]−SˉNPN(q(S)=b), \hat m_b=P_N[S1_{\{q(S)=b\}}]-\bar S_NP_N(q(S)=b),

which converges to mbm_b because SˉN→ES=0\bar S_N\to ES=0. Thus the LLN gives W^b→Wb>0\hat W_b\to W_b>0, m^b→mb\hat m_b\to m_b, so I^λλ→Iq,λλ>κ\hat I_{\lambda\lambda}\to I_{q,\lambda\lambda}>\kappa (eventually ≥κ\ge\kappa), feasibility eventually, and Φ^s→Φ(q)\hat\Phi_s\to\Phi(q) by continuity of the Schur value at a nonsingular scalar nuisance block. Taking qq near the sup gives the floor; the cap of (1) applied to these labelings gives v∗+(κ)≤vK−δ(κ)v^{*+}(\kappa)\le v_K-\delta(\kappa). Neither this approximation nor the price proof supplies an optimizer at the strict boundary or continuity in κ\kappa. ∎

Self-adversarial notes (protocol G). Duplicate atoms and split duplicates are inside the grouping formulation by construction; singleton cells are handled by the mass step, not excluded; I^λλ≥κ\hat I_{\lambda\lambda}\ge\kappa excludes singular nuisance blocks but not det⁡I^N=0\det\hat I_N=0 (such states have Φ^s=0\hat\Phi_s=0, inside the cap trivially); the statement is for exact scores and equal weights — estimated scores are “Estimated scores and classifiers”, unequal weights were probed adversarially at finite NN (census suite) but are not claimed; the law class needs (S) (atomless, unique scalar optimum) — the census grid laws are atomic emulations, evidence only; nothing here claims margin-carrying exchange-stable sequences exist asymptotically (that inhabitation question is OPEN-DS-STABLE-BASINS). Applying qq to centered rows instead of raw SiS_i is a different, sample-dependent labeling convention and needs boundary/translation continuity not assumed here. The PRICE statement is nevertheless pathwise uniform over all labelings, so it covers either convention whenever the margin is observed.

Measured: which regime the optimizer actually occupies

(N-DS-STABLE-CENSUS, N-DS-STABLE-ASCENT, N-DS-STABLE-LIBRARY; py/ds_stable_margins.py, integer-exact full-lattice census selftested against the audit stack's from-scratch oracle on 782 states.)

  • Census (exact, N=10N=10–1414, K=3K=3, centered06 + mix3, 2 reps). Exchange-stable states are plentiful (5–944 per instance) and overwhelmingly non-global. On the centered law they span both regimes: I^λλ\hat I_{\lambda\lambda} from 10−510^{-5} to 0.570.57, with gap and nuisance block anti-correlated (per-instance correlation −0.27-0.27 to −0.83-0.83) — the finite shadow of conclusion (1). Whenever I^λλ>0.2\hat I_{\lambda\lambda}>0.2, the relative gap exceeded 1.2%1.2\%–8.4%8.4\%; margin-retaining non-global stable states existed in every instance (witness fixture CE-DS-STABLE-MARGIN-RETAINING-001, N=8N=8: I^λλ≈0.523\hat I_{\lambda\lambda}\approx0.523, λmin⁡≥0.1397\lambda_{\min}\ge0.1397, min mass 1/41/4, separation 0.3250.325, price 7.7%7.7\%). The DS13 leverage bound held at every spot-checked stable state; the exact sandwich held at all 3,155 stable states censused. (M5) caution: stable states with nearly coincident projected centroids occur (min separation 5.5×10−45.5\times10^{-4}), so separation must be checked, never assumed (cf. DS12 wasted cells).
  • The documented initializer is not a terminal state. The efficient-score DP interval labeling is exchange-unstable in 7/10 centered-law census instances (and already at N=8N=8: fixture CE-DS-INTERVAL-SEED-UNSTABLE-001, exact gain 0.4470.447); the improving move grows the nuisance block 27-fold — near the seed, the profiled objective climbs by buying back nuisance information, the finite face of DS15 Proposition 6's steering. On mix3 the same labeling was stable in 9/10 instances.
  • Exact ascent (N≤14N\le14). Terminal states from the interval seed and 20 random seeds per instance are strongly seed-dependent on the centered law (terminal I^λλ\hat I_{\lambda\lambda} spanning 0.00020.0002–0.570.57); margin-retaining terminals are reached with sizable probability at these tiny NN.
  • Library scale (N=100/300/1000N=100/300/1000, gauss06 vs mix3; efficient-score vs k-means++ vs random seeding; optimize_partition + ProfiledDOptimality + DExchangeConfig, exchange-stable terminals verified). On the centered law, every seeding's terminal state collapses the nuisance block at the predicted K/NK/N scale (N⋅I^λλN\cdot\hat I_{\lambda\lambda} median 0.50.5–3.03.0 across all seeds and sizes) with near-optimal values (the research run's reported aggregate log-gap summaries to the certified DP ceiling are 0.0040.004–0.0460.046; this is not a bound on every seed/run), masses approaching the population values and healthy separations — exactly conclusion (2) in action: the terminals are in the funnel because they are near-optimal in value, seed-independently. On mix3 every seeding lands at λmin⁡≈1.7=Θ(1)\lambda_{\min}\approx1.7=\Theta(1) with log-gaps ≤2×10−4\le2\times10^{-4}: the non-centered regime keeps its margins at the optimum, as OPEN-DS-MARGINS-NONCENTERED's first branch conjectures.

Verdict: the compile rule (DS-PROFILED-COMPILE-CERTIFICATE)

On the conditionally centered class, for what the free optimizer returns:

  • The projected efficient-score interval rule remains the only currently established unconditional compile path in the registered theory. This is an inventory of proved routes, not a mathematical uniqueness theorem about every possible compiler. Free profiled optimization is value-driven; conclusion (2) makes every value-successful run — global or not, however seeded — nuisance-degenerate in the limit, with the companion rule's slope B^z\hat B_z unstable (0/0). Nothing about the terminal state is stably compilable, and compile_quantizer's refusal for profiled criteria is the correct default, now backed by a theorem about the optimizer's actual output rather than only about global optima.
  • DS14 supplies a sequence-conditional companion rule, not a population guarantee from one finite certificate. If an exchange-stable sequence satisfies DS14's full hypotheses — (M1)/(M4) on the law and, eventually, uniform (M2)/(M3)/(M5), or the audited merged-rule variant — then the companion efficient-Voronoi rules ρN\rho_N built from the states' own projected centroids and profiled metrics geometrize and have population-stationary subsequential limits. At one finite NN, exact exchange stability plus measured mass, conditioning, and separation checks are useful diagnostics and define a candidate companion rule, but do not by themselves certify those asymptotics; DS13 is a consequence of stability, not a replacement for it. DS16 prices any state with measured λmin⁡(I^N)≥κ\lambda_{\min}(\hat I_N)\ge\kappa pathwise: report the observable finite gap v^K−Φ^s\hat v_K-\hat\Phi_s (the efficient_score_bound DP ceiling minus the terminal value). The population δ(κ)\delta(\kappa) is existential and may not be reported numerically without a law-specific lower bound. Measured: on the centered class the free optimizer does not return such states at realistic NN (the funnel), so the candidate path operationally appears to require margin-constrained optimization — a solver-design question (an earlier, since-closed question), whose asymptotic non-vacuity (do margin-compatible stable sequences exist? is v∗(κ)v^*(\kappa) attained?) is the explicit open remainder OPEN-DS-STABLE-BASINS (OPEN-DS-STABLE-BASINS).
  • Information-loss implication. A margin-certified compile retains at most vK−δ(κ)v_K-\delta(\kappa) of profiled information against the KK-cell ceiling vKv_K (relative retention ≤1−δ(κ)/vK\le1-\delta(\kappa)/v_K), on top of the binning loss vK<σs2v_K<\sigma_s^2 against unbinned inference; the projected rule attains the ceiling only in the distinct projected-score formulation where nuisance information is supplied externally/unbinned (DS9/DS15 deployability). The theorem gives no positive computable lower bound on δ(κ)\delta(\kappa) from a single finite dataset.

Both study stop conditions that could close the deployment question are thus hit: proved (price + funnel on the stated class) and reduced (the inhabitation/selection remainder is OPEN-DS-STABLE-BASINS), with the falsification half serialized (CE-DS-STABLE-MARGIN-RETAINING-001, CE-DS-INTERVAL-SEED-UNSTABLE-001).

From Profiled Ds: from a sample to the population · chapter contents

Independently audited. The audit report.

Evidence: WORK/artifacts/DS-STABLE-MARGINS-COMPILE/census-summary.json. Measured, never theorem authority.