{"id":"W4280649106","doi":"10.3389/fped.2022.864755","title":"Ignorance Isn't Bliss: We Must Close the Machine Learning Knowledge Gap in Pediatric Critical Care","year":2022,"lang":"en","type":"article","venue":"Frontiers in Pediatrics","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; SickKids Foundation; Institute for Work & Health; Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Harm; Ignorance; BLISS; Health care; Electronic health record; Perspective (graphical); Nursing; Medical education; Medical emergency; Psychology; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0407996,0.0004539475,0.001003352,0.002108861,0.004027831,0.01031189,0.002037064,0.007066793,0.003548031],"category_scores_gemma":[0.1024121,0.000572039,0.0005793297,0.001125952,0.02628427,0.02260188,0.01008923,0.02365348,0.00108921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004920988,"about_ca_system_score_gemma":0.01824645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005913877,"about_ca_topic_score_gemma":0.005939571,"domain_scores_codex":[0.9798276,0.01278026,0.001089333,0.001532025,0.003665016,0.001105843],"domain_scores_gemma":[0.8574059,0.1123129,0.006581496,0.004042716,0.009592155,0.01006482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002571726,0.0003609562,0.02274934,0.002719027,0.0002296963,0.002002519,0.03615075,0.002393079,0.001155528,0.3035222,0.2130766,0.4153831],"study_design_scores_gemma":[0.00004881025,0.0002150649,0.006697286,0.007004332,0.00007824097,0.002056885,0.02255968,0.002141444,0.0008347252,0.7332054,0.2250216,0.0001364324],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00676146,0.02011183,0.01139902,0.9543881,0.001314218,0.00001762883,0.00004684761,0.00005067517,0.005910211],"genre_scores_gemma":[0.4678945,0.07432995,0.04312126,0.4014925,0.009174109,0.0001675962,0.0002194871,0.0002054427,0.003395246],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.0407996,"threshold_uncertainty_score":0.2157715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07667714601955074,"score_gpt":0.382144500540428,"score_spread":0.3054673545208773,"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."}}