{"id":"W2996766745","doi":"10.24507/ijicic.14.06.2129","title":"The predictive modeling for learning student results based on sequential rules","year":2018,"lang":"en","type":"article","venue":"International journal of innovative computing, information & control","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning; Data 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001821855,0.0001259109,0.0001442232,0.0002882408,0.0004410291,0.0006646152,0.001342937,0.00003788962,0.000001647278],"category_scores_gemma":[0.0009968898,0.00009049255,0.0000794167,0.0002818519,0.00007676142,0.001131727,0.0001198218,0.0002680083,0.00001454945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001451128,"about_ca_system_score_gemma":0.0002241663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004414168,"about_ca_topic_score_gemma":6.164025e-7,"domain_scores_codex":[0.997895,0.00006774603,0.001011894,0.0001225975,0.0007255613,0.0001772042],"domain_scores_gemma":[0.9908186,0.0005830168,0.001334863,0.0001733878,0.007046254,0.00004388267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001110487,0.0001557467,0.0002419487,0.000005065461,0.0004716586,0.00000256474,0.004590953,0.3869512,0.00009786908,0.108405,0.00488352,0.4930839],"study_design_scores_gemma":[0.002614561,0.0005710712,0.0006797108,0.00007538445,0.000005135063,0.000009487846,0.0002089534,0.9770117,0.0001461797,0.0006219597,0.01796795,0.00008784256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005275564,0.00000592515,0.9888073,0.003216528,0.00122824,0.0002302339,0.00006847185,0.00003882336,0.001128872],"genre_scores_gemma":[0.9517597,0.000002647658,0.04627819,0.00113634,0.0007540544,0.00001169394,0.00003909305,0.00000498217,0.00001330656],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9464841,"threshold_uncertainty_score":0.6408899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01738670149329674,"score_gpt":0.3153025746708615,"score_spread":0.2979158731775647,"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."}}