{"id":"W4361027137","doi":"10.1016/j.jtha.2023.01.026","title":"Artificial intelligence, science, and learning","year":2023,"lang":"en","type":"editorial","venue":"Journal of Thrombosis and Haemostasis","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Artificial intelligence; Turing; Champion; Computer science; Cognitive science; Field (mathematics); Deep learning; Psychology; Political science; Law; Mathematics","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":[0.01392355,0.004759677,0.006842342,0.007842825,0.004355865,0.01638642,0.004399346,0.01888764,0.012745],"category_scores_gemma":[0.04735816,0.001579556,0.003552379,0.003548349,0.005801273,0.005478464,0.002031149,0.02861184,0.009347029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005701873,"about_ca_system_score_gemma":0.006312142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004275161,"about_ca_topic_score_gemma":0.0152663,"domain_scores_codex":[0.9902242,0.002527348,0.001292805,0.0006609191,0.004861774,0.0004329615],"domain_scores_gemma":[0.9403955,0.03695089,0.001849717,0.001487649,0.01443067,0.00488559],"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":[0.00004131772,0.00001820656,0.00002663155,0.0003381238,0.00003968264,0.00006833828,0.00001506976,0.00004476522,0.00002013123,0.0008295879,0.9923383,0.006219881],"study_design_scores_gemma":[0.0001215421,0.00003363997,0.0003434698,0.001166672,0.0001189323,0.0002204031,0.00008045081,0.0004586396,0.00007537931,0.006204251,0.9911412,0.00003543846],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00001471894,0.01130835,0.0001175977,0.02597973,0.9614218,0.0000105248,0.0000311221,0.00002908933,0.001087081],"genre_scores_gemma":[0.0003235195,0.00739536,0.0001211614,0.01008742,0.9768983,0.00001625563,0.00001793554,0.00002106775,0.005119046],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.01888764,"threshold_uncertainty_score":0.0736357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2329726680036842,"score_gpt":0.4671888977342491,"score_spread":0.2342162297305649,"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."}}