{"id":"W1570060061","doi":"10.1002/0470842555.ch43","title":"Bias and Confounding in Pharmacoepidemiology","year":2000,"lang":"en","type":"other","venue":"Pharmacoepidemiology","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital","funders":"","keywords":"Pharmacoepidemiology; Confounding; Computer science; Econometrics; Medicine; Mathematics; Pharmacology; Internal medicine","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003051078,0.0008006357,0.002340733,0.0009108883,0.0000472753,0.000009113169,0.000480495,0.0009926038,0.006917593],"category_scores_gemma":[0.00354583,0.0007483205,0.000149278,0.0002562159,0.0005433251,0.00008819759,0.0002027749,0.001454467,0.000115064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001011021,"about_ca_system_score_gemma":0.00006347502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005050217,"about_ca_topic_score_gemma":0.0001650226,"domain_scores_codex":[0.9937443,0.002630723,0.001352613,0.001054303,0.0001275931,0.001090447],"domain_scores_gemma":[0.9890862,0.00927847,0.0008616183,0.0005068993,0.0000175901,0.0002492517],"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":[0.00005706313,0.00007339134,0.004642957,0.0002818536,0.0001266866,0.00009719753,0.00007162494,0.00000328124,0.000539399,0.0361251,0.9498038,0.008177663],"study_design_scores_gemma":[0.0008833348,0.00006232688,0.00006173486,0.0003305827,0.0001105693,0.0001089618,0.00001432679,0.0002539283,0.0002479885,0.1951739,0.8020175,0.0007349587],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001854635,0.01051246,0.01037185,0.001901593,0.001259321,0.002148964,0.0001369764,0.002928354,0.9688858],"genre_scores_gemma":[0.01993292,0.1313837,0.17364,0.01916477,0.004744822,0.002047917,0.0003495033,0.00484249,0.643894],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3249919,"threshold_uncertainty_score":0.9994968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4045702089123721,"score_gpt":0.5390313703409946,"score_spread":0.1344611614286225,"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."}}