{"id":"W2340048191","doi":"10.1097/ede.0000000000000487","title":"Targeted Maximum Likelihood Estimation for Pharmacoepidemiologic Research","year":2016,"lang":"en","type":"article","venue":"Epidemiology","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Jewish General Hospital","funders":"Canadian Institutes of Health Research","keywords":"Estimation; Statistics; Maximum likelihood; Mathematics; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.06965593,0.001854098,0.0028374,0.002941196,0.0008573357,0.003175659,0.003130004,0.002714043,0.004775295],"category_scores_gemma":[0.2684712,0.001784154,0.003489826,0.003284428,0.003170824,0.002960662,0.003545912,0.00440852,0.001045934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002232962,"about_ca_system_score_gemma":0.003366763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003487267,"about_ca_topic_score_gemma":0.002016393,"domain_scores_codex":[0.9304606,0.06377798,0.001181875,0.002217477,0.002013934,0.0003480526],"domain_scores_gemma":[0.7701663,0.2112741,0.006508983,0.008574259,0.003014464,0.0004618534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006860879,0.0002829719,0.02432075,0.002158694,0.003713837,0.0007631197,0.0009798902,0.4990937,0.001575873,0.2202063,0.005804902,0.2404137],"study_design_scores_gemma":[0.0002617996,0.0002372955,0.00275102,0.0004394126,0.0002482612,0.000211214,0.00008636776,0.6587913,0.001085917,0.3308058,0.005004834,0.00007670208],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002910138,0.0006090755,0.9950784,0.0004707799,0.00004044685,0.0001575075,0.0000771179,0.0001665745,0.0004899799],"genre_scores_gemma":[0.2526954,0.00160373,0.7409788,0.0008334898,0.00022329,0.001751277,0.0004859608,0.0002895573,0.001138492],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06965593,"threshold_uncertainty_score":0.3683801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5866250288778323,"score_gpt":0.5867883144975042,"score_spread":0.0001632856196719379,"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."}}