{"id":"W6912755582","doi":"10.5291/ill-data.test-3347","title":"HERCULES PRACTICALS: Session A","year":2024,"lang":"en","type":"dataset","venue":"Institut Laue-Langevin","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Session (web analytics); Training (meteorology); Active listening","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity","insufficient_payload"],"category_scores_codex":[0.001068258,0.001151189,0.001163755,0.0008892435,0.0002489279,0.0007038558,0.001335921,0.001330397,0.004931822],"category_scores_gemma":[0.002280165,0.0009569291,0.000399154,0.001091144,0.0004272949,0.0006883619,0.0009479428,0.002665916,0.5494193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005197783,"about_ca_system_score_gemma":0.001137774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009137507,"about_ca_topic_score_gemma":0.002891398,"domain_scores_codex":[0.9946466,0.0004414743,0.0009277042,0.001560444,0.001424457,0.0009992918],"domain_scores_gemma":[0.9962154,0.000413845,0.0004764428,0.002248215,0.0001840785,0.0004620139],"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":[0.00008751679,0.0003675068,0.00000678711,0.00131484,0.00032667,0.003191109,0.0000368678,0.000007903828,0.0001480872,0.000284102,0.993309,0.0009196716],"study_design_scores_gemma":[0.0004004978,0.00008131569,0.00001599119,0.002789804,0.001056047,0.0003714247,0.00006710026,0.00002243043,0.00003933981,0.0002454354,0.9937828,0.001127843],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005897615,0.008435869,0.000005415038,0.000466866,0.003851934,0.001019619,0.9685062,0.0008261462,0.01682897],"genre_scores_gemma":[0.00004172603,0.001095869,0.0003918319,0.0006470518,0.002351413,0.0003167472,0.9929634,0.0002719382,0.001920011],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5444875,"threshold_uncertainty_score":0.9999661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04332781480555793,"score_gpt":0.3541536485421351,"score_spread":0.3108258337365772,"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."}}