{"id":"W4311417400","doi":"10.46747/cfp.6812933","title":"Recognition of inherent biases in administrative data","year":2022,"lang":"en","type":"article","venue":"Canadian Family Physician","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Manitoba Health","funders":"","keywords":"Computer science; Data collection; Data science; Data mining; Information retrieval","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3727083,0.0009369597,0.001951726,0.006222097,0.002762586,0.008315924,0.003996192,0.002137592,0.002101504],"category_scores_gemma":[0.7014604,0.0009946608,0.001448226,0.01359963,0.003846335,0.005878834,0.005140516,0.004604862,0.000667152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004570184,"about_ca_system_score_gemma":0.01169623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02149603,"about_ca_topic_score_gemma":0.0281085,"domain_scores_codex":[0.4785236,0.3790064,0.05296103,0.0160593,0.07062964,0.00281995],"domain_scores_gemma":[0.2302606,0.5806222,0.06342117,0.07270495,0.05100865,0.001982571],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000773096,0.0002161233,0.293425,0.007993625,0.004007332,0.001319644,0.02351136,0.004959419,0.00103382,0.208607,0.08146045,0.3726931],"study_design_scores_gemma":[0.0004108925,0.0004637667,0.1547806,0.01553728,0.002000248,0.003311331,0.01128168,0.01978982,0.004720607,0.3711825,0.4159655,0.0005557822],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08414216,0.02804824,0.670061,0.1369918,0.01107706,0.006010954,0.01530813,0.001093202,0.0472675],"genre_scores_gemma":[0.6108983,0.01117965,0.304953,0.04833947,0.007952304,0.007151642,0.00445683,0.0004850168,0.004583734],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6272917,"threshold_uncertainty_score":0.7735624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3466351137223183,"score_gpt":0.4474343245718259,"score_spread":0.1007992108495076,"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."}}