{"id":"W2510408890","doi":"10.1109/cict.2016.137","title":"Examining Diagnosis Paths: A Process Mining Approach","year":2016,"lang":"en","type":"article","venue":"","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Variety (cybernetics); Process (computing); Data science; Learning analytics; Process mining; Educational data mining; Tracing; Machine learning; Artificial intelligence; Human–computer interaction; Work in process; Business process; Engineering","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":[0.006855468,0.001681564,0.001128817,0.01192603,0.001745048,0.004514533,0.003106528,0.002317138,0.003191271],"category_scores_gemma":[0.03069712,0.0007434403,0.002086759,0.006302226,0.001497589,0.004008366,0.002395341,0.002282718,0.0009638077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001193573,"about_ca_system_score_gemma":0.004371998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007998755,"about_ca_topic_score_gemma":0.006744364,"domain_scores_codex":[0.9953762,0.001780239,0.0005171589,0.001045501,0.001037551,0.0002433524],"domain_scores_gemma":[0.969977,0.02502655,0.001903481,0.001162664,0.001592504,0.0003378855],"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":[0.0005929018,0.002287776,0.1425329,0.001994467,0.0007772464,0.003132218,0.006716184,0.1655686,0.007487216,0.0787199,0.005027333,0.5851632],"study_design_scores_gemma":[0.00009881124,0.0004723543,0.008725998,0.0003905061,0.0003995544,0.001331715,0.00250828,0.8343086,0.006142918,0.1352753,0.01021782,0.0001281123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03068807,0.0004518597,0.9614249,0.001413189,0.00003477695,0.001149785,0.001476375,0.001029888,0.002331088],"genre_scores_gemma":[0.2436698,0.0005737953,0.7518832,0.000188336,0.00004999291,0.0006782328,0.001793513,0.00005883267,0.001104324],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01192603,"threshold_uncertainty_score":0.03625566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03878080647630978,"score_gpt":0.2717938087107987,"score_spread":0.233013002234489,"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."}}