{"id":"W6968161901","doi":"10.5281/zenodo.15538160","title":"Wonkyconn Smoke Test Data","year":2025,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Technologies and Applied Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine","funders":"","keywords":"Smoke; Test (biology); Test data; Cigarette smoke","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007975542,0.003222587,0.001243995,0.002774292,0.001357207,0.002210377,0.003567035,0.002508786,0.08209155],"category_scores_gemma":[0.004250321,0.0008189245,0.001839162,0.005044823,0.0006184056,0.002080107,0.002367078,0.002177767,0.1308727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001617372,"about_ca_system_score_gemma":0.001866114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02399223,"about_ca_topic_score_gemma":0.05526063,"domain_scores_codex":[0.9988871,0.0001397759,0.0000635965,0.00034405,0.0003640799,0.000201338],"domain_scores_gemma":[0.998357,0.0002505879,0.00007672851,0.0005726788,0.0005698411,0.000173092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004593665,0.000018581,0.0003168411,0.0001310127,0.00001727964,0.00001473631,0.00001147449,0.0003841181,0.0001202403,0.0002290959,0.9973083,0.001402444],"study_design_scores_gemma":[0.0003164919,0.00006089576,0.004800056,0.0001294777,0.00004899784,0.0001264477,0.0001138646,0.002712803,0.001546199,0.002897822,0.9871952,0.00005180695],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006898398,0.00008807476,0.0002137268,0.0001282255,0.00009175024,0.00002479295,0.9927524,0.003473423,0.002537734],"genre_scores_gemma":[0.0008796481,0.00003268616,0.00029814,0.00005863574,0.00001200653,0.0000476582,0.9969408,0.0003934377,0.001336881],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9179084,"threshold_uncertainty_score":0.2746236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0588817202467742,"score_gpt":0.2832229448573055,"score_spread":0.2243412246105313,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}