{"id":"W2511113538","doi":"10.4018/978-1-5225-0613-3.ch010","title":"A Dynamic and Scalable Decision Tree Based Mining of Educational Data","year":2016,"lang":"en","type":"book-chapter","venue":"Advances in data mining and database management book series","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Data science; Computer science; Scalability; Big data; Field (mathematics); Data mining; Data stream mining; Process (computing); The Internet; Decision tree; Globe; World Wide Web; Database","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005951441,0.0003495149,0.0003997457,0.000354246,0.0001630483,0.0001690368,0.002956936,0.00007199389,0.00006541776],"category_scores_gemma":[0.00008780988,0.0003166578,0.00001637561,0.0001078213,0.0003298981,0.00680711,0.007743735,0.0001051918,0.000007350985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002572591,"about_ca_system_score_gemma":0.00008782322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007203202,"about_ca_topic_score_gemma":0.0002966964,"domain_scores_codex":[0.9972211,0.00001964143,0.00056079,0.001567675,0.0003615076,0.0002693178],"domain_scores_gemma":[0.9942961,0.0005711133,0.0003504194,0.004648848,0.00003825575,0.0000952325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002946295,0.00004061685,0.0000874895,0.0002828085,0.00004329711,0.00001739329,0.00003992363,0.00000345677,0.000002795049,0.135951,0.01129785,0.852204],"study_design_scores_gemma":[0.0005948433,0.00005361432,0.00009930451,0.002484087,0.00007726022,0.00001361288,0.00008088177,0.04275427,0.000002950688,0.004431658,0.9489166,0.0004908767],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00008610537,0.06606994,0.5749385,0.004140581,0.0008591923,0.001420057,0.05228002,0.0001912256,0.3000143],"genre_scores_gemma":[0.00004868395,0.02617183,0.9016826,0.0001543722,0.00004460115,0.00003454492,0.0146649,0.00003612954,0.05716234],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9376188,"threshold_uncertainty_score":0.9999285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02427566962768486,"score_gpt":0.2914051498074734,"score_spread":0.2671294801797885,"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."}}