{"id":"W4387736624","doi":"10.1186/s12874-023-02060-x","title":"Advancements in predicting and modeling rare event outcomes for enhanced decision-making","year":2023,"lang":"en","type":"editorial","venue":"BMC Medical Research Methodology","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Saskatchewan Health Authority; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rare events; Computer science; Task (project management); Event (particle physics); Data science; Machine learning; Artificial intelligence; Data mining","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch","metaepi_narrow","research_integrity"],"consensus_categories":["metaresearch","research_integrity"],"category_scores_codex":[0.07201509,0.0003912663,0.001761105,0.0006716938,0.0002260645,0.00005514093,0.0008648529,0.001638135,0.0002192173],"category_scores_gemma":[0.9423406,0.0003133584,0.0001646772,0.0004846892,0.0003398649,0.00005914961,0.001115921,0.002936556,0.00001015879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002484063,"about_ca_system_score_gemma":0.001795887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001183085,"about_ca_topic_score_gemma":0.001019937,"domain_scores_codex":[0.9814019,0.009930961,0.001753148,0.001294391,0.004058414,0.001561229],"domain_scores_gemma":[0.3299461,0.668173,0.0002217332,0.0004942589,0.00075736,0.0004075137],"domain_codex":null,"domain_gemma":"methods","domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001754602,0.000250534,0.000536292,0.006213027,0.0001933076,0.0001286961,0.0009147837,0.000128382,0.00004640518,0.02371471,0.2150243,0.7510949],"study_design_scores_gemma":[0.001559271,0.0003391912,0.00004208051,0.004523295,0.00003668459,0.000001249565,0.0004722216,0.1194742,0.00001061217,0.8678265,0.005399899,0.0003147699],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001164962,0.0001834079,0.7575507,0.00006817115,0.2399637,0.0008321888,0.0001161002,0.00005651544,0.00006428955],"genre_scores_gemma":[0.0004066979,0.0007596355,0.902365,0.0000206836,0.09521259,0.0009269833,0.00003098045,0.0001083581,0.0001691069],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8703255,"threshold_uncertainty_score":0.9999319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6326234789922852,"score_gpt":0.6646749732385197,"score_spread":0.03205149424623444,"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."}}