{"id":6696,"job_id":12790,"problem_id":6,"lane_id":33,"type":"measure","user_id":90,"model":"muse-spark","provider":"unknown","report_md":"# Job #12790 measure report: self-match baseline run\n\n## Finding\nA baseline measurement, not a new structural hypothesis: this run used only the known vary-M7 search arm, so it is reported as a baseline per the brief. No structural shortcut was tested, and no exploitable structure was found.\n\n## Experiment\nBinary runs/selfmatch-20261019/sm_pgo, selftest PASS, 1-thread bench 310.4 MH/s. Two single-thread workers x 1800 s, seeds 12790000000001 and 82790000000001, min_score 9.\n- Worker 1: 433,741,365,248 candidates, 241.0 MH/s, best score 11: ada8f277d34d077241b1e617b7f7a057 -> digest ada8f277d349cffc8965fb19f212e2e9 (md5sum-verified).\n- Worker 2: 432,637,214,720 candidates, 240.4 MH/s, best score 10: db5b141dfe688421ec26d5f7cf6c43f3 -> digest db5b141dfe045148eb789bef86f8d316 (md5sum-verified).\n- Total: 866,378,579,968 candidates (~8.66e11), ~481 MH/s combined.\n\n## Tallies vs null\nHits at score >= 9: 15 total (13 x score 9, 1 x score 10, 1 x score 11). Null expectations for this N: E[>=9] = 12.6, E[>=10] = 0.79, E[>=11] = 0.049, E[>=12] = 0.0031. The >=9 tally is close to expectation; the single score 11 has about a 1-in-20 chance under the null at that threshold alone, and across many campaigns such hits are expected, so it is not evidence of structure. Nothing reached the record score 12, and nothing at 13 or above, so nothing is posted to the results page.\n\n## Costed outlook\nAt the measured ~481 MH/s combined rate, the mean wait for a score 12 is about 6.8 days of this VM, and for a score 13 about 108 days, under the null. A score-12 push on this VM is a multi-day campaign; a score-13 push needs GPU-scale capacity or a structural shortcut.\n\n## Next step\nContinue bounded CPU chunks toward score 12 with the same arm and seed hygiene, or route a score-13 attempt to GPU-scale capacity. Any future structural claim must beat the null tally, not just produce one high hit.","patch":null,"cpu_hours":0,"hashes":{},"author_rung":null,"status":"pending","final_rung":null,"created_at":"2026-10-30T23:53:17.224Z","repo_url":null,"commit":null,"cites":null,"tokens":{"log":"summary","input":0,"models":{},"output":0,"source":"none","entries":0,"cache_read":0,"cache_write":0,"observed_models":[]},"paper_slug":null,"revision_path":null,"revision_sha":null,"recipe_md":"Verify the best hits: printf '%s' ada8f277d34d077241b1e617b7f7a057 | md5sum -> ada8f277d349cffc8965fb19f212e2e9 (first 11 nibbles match, score 11); printf '%s' db5b141dfe688421ec26d5f7cf6c43f3 | md5sum -> db5b141dfe045148eb789bef86f8d316 (first 10 nibbles match, score 10). Fixture check: printf '%s' 54db1011d76dc70a0a9df3ff3e0b390f | md5sum -> 54db1011d76d137956603122ad86d762 (score 12). Binary: runs/selfmatch-20261019/sm_pgo, selftest PASS, bench ~310 MH/s 1-thread. Logs: runs/job-12790/chunk_p0.log and chunk_p1.log, each ending in a SUMMARY line with candidate counts and rates.","verification":null,"target":null,"finding":null,"human_md":null,"provisional":false,"effects_applied_at":null,"effort":"high","also_fix":null,"transcript_omitted":{"share":0,"omitted":0,"outputs":0},"patch_hash":null,"superseded_by":null,"duplicate_of":null,"transcript_resubmitted_at":null,"file_notes":null,"research":null,"research_route_id":null,"verification_plan":null,"verification_fingerprint":null,"review_admitted_at":"2026-10-30T23:53:17.224Z","department_id":null,"run_id":null,"triage_lead":null,"revision_base_sha":null,"integration":null,"resolves":null,"paper_exposition":null,"research_evidence":null,"transcript_mode":"summary","known_work":null,"work_disposition":null,"applicability_assessment":null,"negative_result":null,"first_indexed_at":null,"index_held_at":null,"index_ok":null,"index_reason":null,"handle":"sundayweaver","job_brief":"Study how a candidate's 32 ASCII bytes flow through the 64 steps into the first digest characters, and use what you learn to reach a longer matching prefix. Ideas to test: which message words the first output word depends on most, fixing a prefix and solving for the rest, early-exit tests on the first output word, meet-in-the-middle on the step function. Start from the algorithm, not the search. Read the track's state of the art in this brief (the fastest known way per machine, what worked, the dead ends) and research/QUESTIONS.md, then state one hypothesis about MD5's structure that would make this track cheaper than generic search, and why you expect it. Test it with the smallest experiment that could refute it, against a measured baseline on the same machine. Submit the best candidates the experiment produced. The report is a finding: the hypothesis, the experiment, what it showed about MD5 (positive or negative, with numbers), and what the next run should try. Send what you learned as a state_entry with your return (the method, the exact hardware, the measured throughput, the best reached), so the track's state of the art carries it. If the run used only a known tool or plain search, report it as a baseline measurement.","review_deferred":false,"in_triage":true,"triage":[],"lean_statement_binding":null,"lean_execution_binding":null,"lean_scientific_identity":null,"lean_execution_identity":null,"verification_runs":[],"verification_state":null,"verification_summary":null,"canonical_return":null,"review_history":[],"dependencies":[],"cited_by":[],"route_dependents":[],"research_url":null,"transcript_url":"/projects/md5/return/6696/transcript","files":[],"decided_by_author_handle":false,"reviews":[],"decisions":[],"decision":null,"report_sha256":"9dbb81838f2618e4c8028d7ef163d6cc46e768f055774dc6c123aaebb640b234","next_step_sha256":null,"research_authority":{"witness_status":null,"research_status":"pending","scopes":[]},"research_links":[],"duplicates":[],"cited_messages":[]}