{"id":"W2965396085","doi":"","title":"Balancing Student Success and Inferring Personalized Effects in Dynamic Experiments.","year":2019,"lang":"en","type":"article","venue":"Educational Data Mining","topic":"Statistics Education and Methodologies","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02860425,0.001086095,0.001966215,0.001422002,0.0006516948,0.002127412,0.002347097,0.0024138,0.003705818],"category_scores_gemma":[0.1236361,0.0006996255,0.001155017,0.001536065,0.00158453,0.003342137,0.001512037,0.003158962,0.001009948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001061505,"about_ca_system_score_gemma":0.001435457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002174552,"about_ca_topic_score_gemma":0.003626605,"domain_scores_codex":[0.9830213,0.01272955,0.0003367115,0.002774009,0.000638376,0.0005000882],"domain_scores_gemma":[0.7817712,0.1908466,0.006059621,0.01761164,0.001346071,0.002364884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01972896,0.00538373,0.3567983,0.001144824,0.004887772,0.0004625364,0.001073276,0.2519079,0.00951383,0.02825349,0.01367252,0.3071729],"study_design_scores_gemma":[0.000817189,0.00274369,0.08351966,0.0001173502,0.001844384,0.0001846786,0.0002900418,0.7873411,0.00626603,0.112104,0.004648418,0.0001234642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7118937,0.001923678,0.2716289,0.002689088,0.0003570255,0.0007009828,0.003777267,0.001709933,0.005319338],"genre_scores_gemma":[0.968982,0.0001543417,0.02690043,0.0004844608,0.0001855518,0.0004395577,0.001320848,0.0001110881,0.001421875],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02860425,"threshold_uncertainty_score":0.1512756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1691349651200919,"score_gpt":0.4997090568121423,"score_spread":0.3305740916920505,"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."}}