{"id":"W3092538788","doi":"10.1016/j.patter.2020.100119","title":"Inference and Prediction Diverge in Biomedicine","year":2020,"lang":"en","type":"article","venue":"Patterns","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Mila - Quebec Artificial Intelligence Institute; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Seventh Framework Programme; RWTH Aachen University; National Institute on Aging; Deutsche Forschungsgemeinschaft; National Institutes of Health; National University of Singapore; Amazon Web Services; Institut national de recherche en informatique et en automatique (INRIA); Canadian Institute for Advanced Research; Google","keywords":"Biomedicine; Inference; Artificial intelligence; Computer science; Biology; Bioinformatics","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":[],"consensus_categories":[],"category_scores_codex":[0.00008847651,0.0000539737,0.00007465484,0.00004971259,0.00002514403,0.00002212192,0.0002055049,0.00002506593,0.00002589523],"category_scores_gemma":[0.00009475243,0.00004910535,0.000006696886,0.0001839643,0.00001046552,0.000126335,0.0001902668,0.0001464698,0.00001910378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001183518,"about_ca_system_score_gemma":0.0000136603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002675625,"about_ca_topic_score_gemma":0.00005572248,"domain_scores_codex":[0.9993903,0.00004738043,0.0001155015,0.0002125598,0.0001178054,0.0001164775],"domain_scores_gemma":[0.9996878,0.00005099057,0.00002864431,0.0001254384,0.00001383594,0.00009331878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001151906,0.000004553571,0.9791363,0.00004843618,9.248055e-7,0.00001155881,0.002421096,0.00002296922,0.00006897539,0.0003778608,0.00006077018,0.01784542],"study_design_scores_gemma":[0.0001784652,0.00008461631,0.8311299,0.00003444431,6.561081e-7,0.000002501386,0.00002362878,0.1676044,0.00002808214,0.0001066397,0.0007602996,0.00004632753],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7097526,0.00007867384,0.2670644,0.0225066,0.0001932428,0.0001043593,0.000008253192,0.0001412659,0.0001506648],"genre_scores_gemma":[0.9975744,0.00002784976,0.0007893764,0.001516669,0.00007198358,0.000004901408,0.000003369391,0.000002793358,0.000008631672],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2878219,"threshold_uncertainty_score":0.2002458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03130443943549634,"score_gpt":0.2871782830493894,"score_spread":0.255873843613893,"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."}}