{"id":"W6954847496","doi":"10.57745/kwl6u9","title":"Data_Second_Set_Analyses_SubsequentNight-Day.csv","year":2024,"lang":"en","type":"dataset","venue":"Recherche Data Gouv France","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Clinical Research Institute","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.01095424,0.001855061,0.002047048,0.0009694985,0.0002339899,0.001052723,0.01602692,0.003391411,0.009953246],"category_scores_gemma":[0.005111532,0.001765649,0.0003987823,0.003473172,0.0004834708,0.002019219,0.006265667,0.009745094,0.4900771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001311951,"about_ca_system_score_gemma":0.001589789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002827457,"about_ca_topic_score_gemma":0.005163608,"domain_scores_codex":[0.9870028,0.003092674,0.001724352,0.004719389,0.001733812,0.001726951],"domain_scores_gemma":[0.9758075,0.001974346,0.0007855377,0.02058511,0.000252116,0.0005953131],"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":[0.00003164784,0.0001973039,0.000004923812,0.001110549,0.001072024,0.0006444826,0.00004532726,0.00000314697,0.0002140294,0.00001879681,0.9940289,0.002628875],"study_design_scores_gemma":[0.0004077045,0.00003911554,0.000008898491,0.0007844358,0.001678555,0.00009082246,0.00004761777,0.0006682503,0.00006661347,0.0006852772,0.9935871,0.00193562],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00000764273,0.02281306,0.00009891228,0.000327152,0.002943584,0.0008375551,0.9711741,0.0007314984,0.001066553],"genre_scores_gemma":[0.000001101149,0.007612769,0.002514779,0.00101413,0.002328104,0.0001322733,0.9805403,0.0005454039,0.005311178],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4801239,"threshold_uncertainty_score":0.9999843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4046806296478613,"score_gpt":0.4505496757884797,"score_spread":0.04586904614061837,"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."}}