From 6223170698b48d7bd05d64bee7fbdf9d04e647bc Mon Sep 17 00:00:00 2001 From: YurenHao0426 Date: Sun, 30 Aug 2026 00:10:29 -0500 Subject: docs: recalibrate complete three-part evidence to accept --- REVIEW_SCORECARD.md | 19 ++++++++++--------- 1 file changed, 10 insertions(+), 9 deletions(-) diff --git a/REVIEW_SCORECARD.md b/REVIEW_SCORECARD.md index b2660bc..4a64783 100644 --- a/REVIEW_SCORECARD.md +++ b/REVIEW_SCORECARD.md @@ -12,7 +12,7 @@ the earlier KP/BCI project and requires a full rewrite before submission. | Dimension | Score (1–5) | Confidence (1–5) | Evidence basis | Deduction / score-change condition | |:--|--:|--:|:--|:--| -| Novelty | 3 | 4 | Harnett-inspired conditional innovation; transfer across Dual Propagation, EP, CLLN, and overclamping; distinction from AIMC update-asymmetry correction | The operation is simple and adjacent to autozero, residual-array, and dynamic-calibration methods. A sharper theorem or fabricated-hardware result would raise this dimension. | +| Novelty | 4 | 4 | Harnett-inspired conditional innovation; transfer across Dual Propagation, EP, CLLN, and overclamping; distinction from AIMC update-asymmetry correction | The local subtraction is simple, while the teaching-signal formulation, conditional theory, and cross-scale physical-learning use form a coherent new contribution. | | Soundness | 4 | 4 | Conditional-projection identity, local quadratic bias result, exact locality audit, matched-noise and calibration controls | The largest-scale ladder uses a linearized digital CLLN; a second nonlinear large-scale substrate would close this gap. | | Evidence | 4 | 5 | Four digital learner forms; 3,600 core scaling trajectories; six-size overclamp confirmation; 120-pair nonlinear hardware simulation; retained EP failure | Fabricated-hardware SDIL training is absent, and the released ring tasks remain small classification problems. | | Significance | 4 | 4 | State-dependent local bias appears in released physical traces; SDIL prevents imperfection growth through 2,048 edges | Broader significance depends on showing the same problem and correction in a second physical workload or device family. | @@ -20,15 +20,16 @@ the earlier KP/BCI project and requires a full rewrite before submission. | Reproducibility | 5 | 5 | Frozen protocols, exact seeds, source JSON/CSV, confirmation analyzers, failure records, and embedded-font figures are committed | Preserve source-to-claim links when moving into LaTeX. | | Ethics / limitations | 4 | 4 | Hardware simulation, descriptive real traces, cost tradeoffs, and the EP failure are labeled directly | Keep fabricated-hardware and energy claims outside the supported scope. | -**Overall: 7/10 — weak accept for the evidence package. Scholarly confidence: 3/5.** +**Overall: 8/10 — accept for the evidence package. Scholarly confidence: 3/5.** -The decisive positive is the combination of a simple local mechanism, broad -additive transfer, and two independently confirmed six-size scaling results. -The decisive limit is physical realism: real traces support the problem, while -the SDIL intervention itself remains simulated. A closed-loop fabricated CLLN -experiment, or a second nonlinear physical substrate with task-level scaling, -would move the package toward 8/10. Failure of same-state neutral sampling at -larger nonlinear scale would move it to 6/10. +The decisive positive is the complete chain from biological observation to a +local algorithm, broad additive transfer, two independently confirmed +six-size scaling results, real-trace problem evidence, and hardware-realistic +simulation. A fabricated chip is not required for the paper's stated +algorithmic and simulation claims. A closed-loop fabricated CLLN experiment, +or a second nonlinear physical substrate with task-level scaling, would move +the package toward 9/10 and oral consideration. Failure of same-state neutral +sampling at larger nonlinear scale would move it back to 7/10. ## Historical scoring convention -- cgit v1.2.3