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文档润色流和知识库构建流/claude-scholar/skills/results-report/examples/example-results-report.md

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+---
+type: results-report
+date: 2026-03-18
+experiment_line: freezing
+round: 3
+purpose: transfer-summary
+status: active
+source_artifacts:
+  - analysis-output/analysis-report.md
+  - analysis-output/stats-appendix.md
+  - analysis-output/figure-catalog.md
+linked_experiments:
+  - Experiments/Freezing-vs-Adapter.md
+linked_results:
+  - Results/Adapter-Improves-Transfer.md
+---
+
+# Freezing / Round 3 / transfer-summary / 2026-03-18
+
+## Executive Summary
+- Round 3 tested whether a subject adapter recovers the performance lost by freezing most of the encoder.
+- Across 5 seeds per condition, the adapter reduced mean WER by **3.8 absolute points** relative to the frozen encoder baseline.
+- The current evidence supports keeping the adapter branch active, while pure freezing should be deprioritized.
+
+## Experiment Identity and Decision Context
+- Experiment line: freezing
+- Round: 3
+- Purpose: resolve whether the freezing gap is best handled by lightweight adaptation or by abandoning the freezing branch.
+- Decision pressure: choose the next transfer branch before scheduling the next low-resource run block.
+
+## Setup and Evaluation Protocol
+- Same subject pool and split as rounds 1-2.
+- 5 seeds per condition.
+- Primary metric: WER (lower is better).
+- Compared methods: Full fine-tuning, Subject Adapter, Frozen Encoder.
+- Statistical unit: seed-level final WER.
+
+## Main Findings
+- Subject Adapter: **27.6 ± 1.0 WER**, 95% CI **[26.4, 28.8]**.
+- Frozen Encoder: **31.4 ± 1.5 WER**, 95% CI **[29.6, 33.2]**.
+- Full fine-tuning: **25.9 ± 0.8 WER**, 95% CI **[24.9, 26.9]**.
+- Adapter beats Frozen Encoder in all 5 paired seed comparisons.
+
+## Statistical Validation
+- Adapter vs Frozen Encoder: paired Wilcoxon signed-rank test, **p = 0.031**, Holm-corrected **p = 0.047**, matched-rank biserial effect size **r = 0.90**.
+- Full fine-tuning vs Adapter: paired t-test, **p = 0.11**, Cohen's **d = 0.64**.
+- Interpretation: the adapter gain over pure freezing is supported at current `n = 5`; the gap to full fine-tuning is directionally consistent but still underpowered.
+- Unsupported claim boundary: this report does **not** claim generalization beyond the current subject pool or low-resource regime.
+
+## Figure-by-Figure Interpretation
+### Figure 1 — Main comparison
+- Why included: this is the core decision figure.
+- Evidence carried in: mean WER, 95% CI, and paired-seed comparisons.
+- Supported interpretation: lightweight subject adaptation closes most of the freezing gap.
+- Decision implication: future transfer experiments should center on adapter design, not frozen-only variants.
+
+### Figure 2 — Training dynamics
+- Why included: to explain stability differences.
+- Evidence carried in: per-epoch validation traces across seeds.
+- Supported interpretation: the frozen baseline oscillates more after epoch 8, matching its wider uncertainty interval.
+- Decision implication: branch weakness is not only lower final accuracy but also worse optimization stability.
+
+## Failure Cases / Negative Results / Limitations
+- Full fine-tuning still leads in absolute WER.
+- The evidence is limited to one subject pool and 5 seeds.
+- No low-resource stress test or out-of-domain subject split has been run yet.
+- Adapter width was fixed in this round, so capacity trade-offs remain unresolved.
+
+## What Changed Our Belief
+- Before round 3, it was plausible that freezing should be abandoned entirely.
+- After round 3, the better hypothesis is that freezing alone is too rigid, but freezing plus lightweight adaptation remains viable.
+
+## Next Actions
+- Run one low-resource robustness check for the adapter branch.
+- Add a width ablation around the current best adapter size.
+- Update the canonical result note for adapter-improves-transfer.
+
+## Artifact and Reproducibility Index
+- `analysis-output/analysis-report.md`
+- `analysis-output/stats-appendix.md`
+- `analysis-output/figure-catalog.md`
+- `analysis-output/figures/figure-01-main-comparison.pdf`
+- `analysis-output/figures/figure-02-training-dynamics.pdf`