{"id":"W2600361628","doi":"10.1016/j.jclinepi.2017.02.017","title":"Quasi-experimental study designs series—paper 7: assessing the assumptions","year":2017,"lang":"en","type":"article","venue":"Journal of Clinical Epidemiology","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":150,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Economic and Social Research Council","keywords":"Causal inference; Regression discontinuity design; Instrumental variable; Series (stratigraphy); Inference; Randomized experiment; Research design; Popularity; Computer science; Econometrics; Clinical study design; Interrupted time series; Quasi-experiment; Management science; Medicine; Statistics; Mathematics; Psychology; Machine learning; Artificial intelligence; Clinical trial; Social psychology; Engineering; Environmental health","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03530513,0.0002055372,0.001888478,0.00005167072,0.0005913767,0.00007089138,0.001107753,0.0002718698,0.0001869375],"category_scores_gemma":[0.1709183,0.0001174088,0.0005268463,0.00003562041,0.0007518805,0.0009206443,0.0002632495,0.001432944,0.00001537842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005797222,"about_ca_system_score_gemma":0.0001620231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001738701,"about_ca_topic_score_gemma":0.00002573473,"domain_scores_codex":[0.9894304,0.005768728,0.003954417,0.0002449313,0.0002460587,0.0003554922],"domain_scores_gemma":[0.9528551,0.03987134,0.005788577,0.001012286,0.0002845266,0.0001881862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003820795,0.01534256,0.6409938,0.00003080168,0.0008287163,0.0002400408,0.0007588294,0.000034644,0.000932865,0.3084839,0.02046565,0.0115061],"study_design_scores_gemma":[0.001016845,0.007328543,0.1782104,0.0001032749,0.0001759602,0.0002527361,0.001524343,0.0001162369,0.0002070381,0.8073596,0.003480217,0.0002247919],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8052911,0.0001825085,0.1767845,0.01301012,0.001601323,0.0004829642,0.000002413768,0.00007574673,0.002569286],"genre_scores_gemma":[0.8908494,0.0001007839,0.1070785,0.0009099212,0.0008488764,0.00001377069,2.422668e-7,0.00002304027,0.0001754403],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4988757,"threshold_uncertainty_score":0.9933563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8002265442453002,"score_gpt":0.6851954560928973,"score_spread":0.1150310881524028,"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."}}