{"id":"W2372922109","doi":"","title":"An Application of Association Rules In Analysis of Instruction Evaluation Data","year":2005,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Educational Technology and Assessment","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Credibility; Objectivity (philosophy); Association rule learning; Field (mathematics); Raising (metalworking); Data mining; Data science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.02163474,0.001343904,0.002380812,0.01310378,0.001674234,0.004294302,0.001940017,0.00166964,0.001727376],"category_scores_gemma":[0.07374375,0.001024233,0.002715898,0.0118117,0.001403964,0.004898441,0.00158352,0.002568304,0.001240271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009887255,"about_ca_system_score_gemma":0.00306665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008232278,"about_ca_topic_score_gemma":0.005071216,"domain_scores_codex":[0.9712507,0.01253805,0.003848067,0.0039704,0.00780268,0.0005901479],"domain_scores_gemma":[0.9045538,0.0790562,0.003563157,0.004618647,0.007450415,0.0007578348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006145184,0.000757279,0.04309397,0.0007203026,0.001177075,0.0009264136,0.001236496,0.04201045,0.005464293,0.02101306,0.005528817,0.8774573],"study_design_scores_gemma":[0.0001769484,0.0004548345,0.02307023,0.0003911422,0.0009027871,0.002146986,0.0008300339,0.8470426,0.01392545,0.090772,0.01991843,0.0003684604],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01896477,0.0005036914,0.9758203,0.0004457578,0.00009181277,0.0003244075,0.0007167076,0.002165926,0.0009666094],"genre_scores_gemma":[0.09671005,0.0004235846,0.9003368,0.0001260628,0.00008134266,0.000440284,0.001096487,0.0001103595,0.0006750149],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02163474,"threshold_uncertainty_score":0.1144168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0216824962310909,"score_gpt":0.3492533819485323,"score_spread":0.3275708857174414,"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."}}