AXIOM BOINC SESSION RESULTS
Session: p3_save_upload_2026-03-04_0450
Date: March 4, 2026, 04:50

PART 1 VALIDATION/CREDIT SUMMARY (from validate_2026-03-04_0446.txt)
- Results reviewed: 268 successful rows across two runtime-tier credit batches.
- Credit awarded this session: 2057 total (credit-cap check passed).
- Top credited users: Amapola (1301), Steve Dodd (505), Orange Kid (121), ChelseaOilman (50), others smaller.
- Upload artifact audit: 0 payload JSON files found for the credited rows.
- Website counters after update: credited_count=6731, total_results_count=1344.

STUCK/BROKEN TASK CLEANUP
- Broken-family abort sweep (server_state IN (2,4)):
  exp_oscillatory_roughchannel_lbm_resonance*=0,
  exp_abx_cycle*=0,
  exp_potts_pulse_anneal_resonance*=0,
  exp_spatial_pgg_delay_fatigue*=0.
- Stuck-task cleanup:
  >12h on dead hosts (>6h no contact)=0,
  >48h hard-ceiling aborts=0.

PART 2 DEPLOYMENT/RESEARCH SUMMARY (from run_2026-03-03_1352.log + DB checkpoint)
- Retirement pass executed; no unsent retire-aborts were needed (ABORT_TOTAL=0).
- New CPU experiment script authored and uploaded: wd_batchnoise_interaction.py (py_compile OK).
- CPU deployment run:
  hosts seen=81, skipped for RAM<6GB=2, CPU workunits created=2937.
  CPU scripts used: wd_batchnoise_interaction.py and wd_labelsmooth_interaction.py.
  Targeting policy: fill to ~3x CPU core queue per eligible host.
- GPU deployment run in Part 2 was interrupted in log (^C), so checkpointed from DB now:
  GPU scripts in use: wd_curvature_trigger_gpu.py and wd_timing_scale_gpu.py.
  Active queued GPU tasks currently: 21 across 10 GPU hosts.
  Hosts currently carrying queued GPU tasks: Pyhelix, W10-Home, DESKTOP-DUVULOS, DESKTOP-P57624Q, achernar, DESKTOP-N5RAJSE, Foxtrot-2, DESKTOP-ELBSBOI, Thing0L_4000, Raimund-PC.
  GPU tasks sent since 2026-03-03 13:00 for these scripts: 84 total across 12 hosts (47 curvature + 37 timing).

NEW EXPERIMENTS + NOVELTY CHECK DOCUMENTATION
1. wd_batchnoise_interaction.py
- Hypothesis: late weight-decay benefit should be stronger under small-batch gradient noise than large-batch conditions.
- Novelty-search trail logged in Part 2 run:
  - site:arxiv.org weight decay label smoothing interaction
  - site:arxiv.org adaptive weight decay deep neural networks
  - site:arxiv.org batch size weight decay generalization
  - "weight decay" "batch size" "schedule" neural networks
  - arxiv 1711.05101 decoupled weight decay regularization
- Novel angle used for deployment: explicit interaction test (batch-noise x late-WD timing), not just standalone WD schedule benchmarking.

KEY SCIENTIFIC FINDINGS
1. No new contradictory evidence against the previously observed inverse critical-period / WD timing signal appeared in this validation pass.
2. Data-ingestion reliability remains the main blocker: this session credited 268 rows but payload artifacts were missing in audit.
3. Broken-prefix families continue producing non-informative failures (often empty stderr), while targeted cleanup found no currently abortable stuck/broken rows.
4. The active research queue is focused on WD interaction mechanisms (batch-noise interaction, curvature-triggered timing) with continued GPU participation.

NOTES
- This log intentionally summarizes in bulk by experiment family and does not include cumulative credited result-ID lists.