{"id":"W4210732551","doi":"10.1016/j.injury.2022.01.046","title":"Machine learning and artificial intelligence in research and healthcare","year":2022,"lang":"en","type":"article","venue":"Injury","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":184,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Artificial intelligence; Computer science; Machine learning; Health care; Process (computing); Categorization; Expansive; Quality (philosophy); Data quality; Data science; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.001411395,0.00006637706,0.0001372609,0.0003184722,0.0004178004,0.00002010812,0.00004427998,0.00004682505,0.0002023429],"category_scores_gemma":[0.0002846648,0.00006929765,0.0000112649,0.0004883753,0.0001264442,0.00004543802,0.0001240016,0.0009893522,0.00001291821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001411423,"about_ca_system_score_gemma":0.0001598912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003947735,"about_ca_topic_score_gemma":0.000424705,"domain_scores_codex":[0.9986615,0.0002259174,0.000296962,0.0002614493,0.0002741053,0.0002801255],"domain_scores_gemma":[0.9994133,0.0002236633,0.00003252355,0.0001056995,0.00009538024,0.0001294941],"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":[0.0004532541,0.0001374487,0.1588805,0.00009869926,0.000003406441,0.00002842074,0.005198365,0.000007018995,0.0006961732,0.007653712,0.0001016952,0.8267413],"study_design_scores_gemma":[0.0001984337,0.02187943,0.05329187,0.0006861715,0.00004130757,0.0008467263,0.2051598,0.03905963,0.03296607,0.5103828,0.134264,0.001223659],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795104,0.002725666,0.00003009265,0.01679939,0.000193029,0.0003341297,0.000005813957,0.00002633641,0.0003751036],"genre_scores_gemma":[0.9983361,0.0006703,0.000147236,0.0003414553,0.0001325038,0.0000703524,0.00001503184,0.00001193519,0.0002750957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8255177,"threshold_uncertainty_score":0.596782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.360634918034744,"score_gpt":0.5356350568569345,"score_spread":0.1750001388221905,"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."}}