{"id":"W6913164945","doi":"10.5683/sp3/0xywk3","title":"Health Information Research Unit AutoML 2024","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Relevance (law); Rigour; Unit (ring theory); MEDLINE; Cover (algebra); Clinical Practice; Information system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004549883,0.002385679,0.002197539,0.0114251,0.001284998,0.004753221,0.003660869,0.003182393,0.1290423],"category_scores_gemma":[0.04049199,0.0009691318,0.001725929,0.01362287,0.0008552908,0.001782106,0.003484515,0.002378101,0.125817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002420133,"about_ca_system_score_gemma":0.00565371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01286344,"about_ca_topic_score_gemma":0.02838174,"domain_scores_codex":[0.995097,0.001396395,0.001293957,0.0009165111,0.0009286983,0.0003674371],"domain_scores_gemma":[0.9832014,0.008684904,0.002228135,0.002580462,0.00232856,0.0009764914],"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":[0.0002408796,0.00004839336,0.001041965,0.005958301,0.00009002482,0.00008160576,0.00008701847,0.0003607678,0.0002368174,0.001242785,0.9846259,0.005985616],"study_design_scores_gemma":[0.0006553577,0.00006287484,0.002113462,0.001623627,0.0001180087,0.0001624446,0.0001129516,0.0004420536,0.0004399469,0.002208198,0.9920209,0.00004016544],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001516182,0.0001905721,0.0001348877,0.0001300453,0.00002830676,0.00006657309,0.9980949,0.0002933468,0.0009096864],"genre_scores_gemma":[0.0005982609,0.0001661874,0.0009843212,0.0001517829,0.00001699143,0.0004308048,0.9967457,0.00008674613,0.0008191248],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1290423,"threshold_uncertainty_score":0.4316896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0853379951625276,"score_gpt":0.4214091547693742,"score_spread":0.3360711596068466,"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."}}