{"id":"W4393687373","doi":"10.5281/zenodo.6376543","title":"MaMI dataset","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University","funders":"","keywords":"Computer science","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","sts","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002208944,0.0003208984,0.0003908318,0.000475228,0.01418607,0.0002359442,0.003156682,0.00037202,0.8001813],"category_scores_gemma":[0.002592629,0.0003554884,0.00007788004,0.0007556708,0.0002190662,0.0001949048,0.006503548,0.003151471,0.1116651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008925775,"about_ca_system_score_gemma":0.000044485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001539517,"about_ca_topic_score_gemma":0.00003828979,"domain_scores_codex":[0.9932823,0.003076044,0.0008964767,0.0008707775,0.0008815156,0.0009929504],"domain_scores_gemma":[0.9963281,0.0002371517,0.0005095653,0.001839469,0.0006964898,0.0003892566],"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":[0.00006934578,0.00009845512,0.000001359956,0.0005540096,0.00003444298,0.00005169888,0.0004603859,0.000007259057,0.00001012929,0.00029669,0.9912523,0.007163916],"study_design_scores_gemma":[0.0001386394,0.0002146977,0.00001408765,0.00008931697,0.00003162587,0.00003093446,0.001680488,0.00002365771,0.000002816316,0.000132912,0.9973221,0.0003186724],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004215026,0.000119229,0.00003628746,0.001176424,0.001102272,0.001515783,0.9857581,0.0006307538,0.009619058],"genre_scores_gemma":[0.00005887276,0.0004879742,0.00002268741,0.001587985,0.000675411,6.036526e-7,0.9942505,0.001891606,0.001024349],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6885162,"threshold_uncertainty_score":0.9998897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.203151940486132,"score_gpt":0.438719707218919,"score_spread":0.2355677667327869,"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."}}