{"id":"W4313705379","doi":"10.1093/jalm/jfac124","title":"Diving into Data Science: A Clinical Laboratory Update","year":2023,"lang":"en","type":"article","venue":"The Journal of Applied Laboratory Medicine","topic":"Clinical Laboratory Practices and Quality Control","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital; University of British Columbia","funders":"","keywords":"Library science; Medical laboratory; Medicine; Pathology; Computer science","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":[0.03772337,0.002353233,0.003368647,0.01320313,0.002316735,0.01217121,0.007411,0.01377863,0.009487039],"category_scores_gemma":[0.100594,0.001815311,0.003014585,0.01373365,0.008209177,0.0282757,0.007726013,0.03500552,0.007920315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009412487,"about_ca_system_score_gemma":0.01356852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007397315,"about_ca_topic_score_gemma":0.01140408,"domain_scores_codex":[0.9841076,0.004368187,0.003192645,0.001756548,0.005857398,0.0007176562],"domain_scores_gemma":[0.8453942,0.07036732,0.005966873,0.005549752,0.06062638,0.0120955],"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":[0.00005680544,0.00006868027,0.0003012258,0.001030096,0.00005119665,0.0001331189,0.0001241082,0.0001582112,0.0001216894,0.007059204,0.8359558,0.1549399],"study_design_scores_gemma":[0.00001824384,0.00003251922,0.0002849321,0.002025889,0.00002719812,0.0002918382,0.00008624879,0.0001051495,0.00005507975,0.002349881,0.9946945,0.00002850676],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.0002597352,0.4697781,0.004204783,0.4180081,0.1011327,0.0000729483,0.0003570627,0.0005547072,0.00563186],"genre_scores_gemma":[0.002546108,0.6237022,0.01003378,0.1974789,0.157753,0.0002129478,0.001162192,0.0003542459,0.006756696],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03772337,"threshold_uncertainty_score":0.1995026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1214743868408944,"score_gpt":0.4624828836685302,"score_spread":0.3410084968276358,"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."}}