{"id":"W3009124718","doi":"10.1145/3372161","title":"Evidence that computer science grades are not bimodal","year":2019,"lang":"en","type":"article","venue":"Communications of the ACM","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University","funders":"","keywords":"Categorization; Psychology; Mathematics education; Computer science; Artificial intelligence","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":[0.006377334,0.0002849048,0.0002984022,0.001919596,0.0006409517,0.001848049,0.0009334913,0.001124569,0.01476737],"category_scores_gemma":[0.1286249,0.0003114826,0.0002506447,0.001309333,0.002817988,0.001700082,0.001984813,0.001219467,0.001435418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006226547,"about_ca_system_score_gemma":0.0005596056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001977443,"about_ca_topic_score_gemma":0.001793218,"domain_scores_codex":[0.9923665,0.00230201,0.0007451277,0.001555285,0.002529076,0.000501875],"domain_scores_gemma":[0.7729778,0.1191118,0.06014504,0.01861118,0.02193386,0.007220339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001805467,0.0002001468,0.9467675,0.0002504893,0.00015887,0.0001438287,0.003009519,0.0002666391,0.00454548,0.005279159,0.001210646,0.03636219],"study_design_scores_gemma":[0.00005552894,0.0004960666,0.9848408,0.0001001566,0.00005286152,0.0003834399,0.002188775,0.0006973952,0.003269065,0.004625182,0.003250766,0.00004009828],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827953,0.0003720451,0.00229357,0.001080304,0.00003676916,0.00001903886,0.0004183329,0.00006269054,0.01292197],"genre_scores_gemma":[0.999136,0.00004471251,0.0002009264,0.0001347222,0.00001804169,0.000006785666,0.0001212638,0.000008503489,0.0003290713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01476737,"threshold_uncertainty_score":0.04940182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1354539951158094,"score_gpt":0.3293536276572384,"score_spread":0.193899632541429,"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."}}