{"id":"W4394904735","doi":"10.56367/oag-042-11365","title":"AI healthcare research: Pioneering iSMART Lab","year":2024,"lang":"en","type":"article","venue":"Open Access Government","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Health care; Healthcare system; Political science; Engineering ethics; Library science; Engineering; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.03452868,0.001516161,0.000984443,0.003271281,0.003598549,0.01500597,0.001894159,0.008378785,0.01676452],"category_scores_gemma":[0.03720757,0.0008086413,0.001032757,0.001709609,0.009173479,0.009667622,0.00482305,0.02057291,0.01411855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009114843,"about_ca_system_score_gemma":0.0230576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008188541,"about_ca_topic_score_gemma":0.01125006,"domain_scores_codex":[0.9801896,0.00604727,0.0009211159,0.002259359,0.008872172,0.001710502],"domain_scores_gemma":[0.9123975,0.01658355,0.001740976,0.004158211,0.03068439,0.03443537],"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":[0.00007945106,0.0001368033,0.000515323,0.0001786628,0.00002498882,0.0001586254,0.000370021,0.0001699183,0.0006532029,0.03462057,0.8867964,0.07629595],"study_design_scores_gemma":[0.00003320506,0.0000674743,0.0003333526,0.0004601883,0.00001661638,0.0002720745,0.000203939,0.0003553766,0.0008056643,0.0116384,0.9857778,0.00003597387],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.001188833,0.05732041,0.008030258,0.8342607,0.03653453,0.00006873778,0.0001730614,0.0006161662,0.06180723],"genre_scores_gemma":[0.05384272,0.1241822,0.03863508,0.4093959,0.1086111,0.0003020429,0.0007099684,0.001575257,0.2627459],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03452868,"threshold_uncertainty_score":0.1826074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6339883439702305,"score_gpt":0.642261489466969,"score_spread":0.008273145496738521,"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."}}