{"id":"W7047545107","doi":"","title":"Evaluating kindergarten retention policy: A case study of causal inference for multilevel observational data","year":2014,"lang":"en","type":"article","venue":"","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Causal inference; Observational study; Causal model; Multilevel model; Class (philosophy); Term (time); Normative","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06107247,0.0004499729,0.001152041,0.001770545,0.004432561,0.003284473,0.002727696,0.003146115,0.004862071],"category_scores_gemma":[0.2687963,0.0008272944,0.001010315,0.005735131,0.003673694,0.002407641,0.002604279,0.003010511,0.0001367151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02315072,"about_ca_system_score_gemma":0.0218296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.497921,"about_ca_topic_score_gemma":0.4802687,"domain_scores_codex":[0.9289451,0.06401772,0.001739265,0.001712548,0.00218847,0.001396975],"domain_scores_gemma":[0.4567929,0.5102035,0.01166159,0.00973729,0.008939204,0.002665575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001646146,0.0009013808,0.5255743,0.001363811,0.002005476,0.006050938,0.04528513,0.08768372,0.0004955888,0.16416,0.01949429,0.1453393],"study_design_scores_gemma":[0.00111931,0.001768664,0.2761877,0.002553527,0.002230822,0.0007073107,0.07163697,0.4277601,0.003763926,0.1691395,0.04261692,0.0005154036],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8547282,0.005251864,0.08321147,0.03917743,0.0001840676,0.001717406,0.002706495,0.0002337885,0.01278921],"genre_scores_gemma":[0.9712592,0.0009634686,0.02586351,0.0002497783,0.00003087136,0.0003202092,0.000259656,0.00002132425,0.00103196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.497921,"threshold_uncertainty_score":0.9900455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4035657516617621,"score_gpt":0.4855761119634429,"score_spread":0.08201036030168085,"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."}}