{"id":"W92525427","doi":"10.4018/978-1-60566-010-3.ch230","title":"Pattern Discovery as Event Association","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pattern Discovery Technologies (Canada); University of Waterloo","funders":"","keywords":"Event (particle physics); Association (psychology); Task (project management); Mathematics; Binary number; Computer science; Artificial intelligence; Combinatorics; Algorithm; Natural language processing; Arithmetic; Psychology; Physics","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":[0.0001433319,0.0002865193,0.0002709255,0.00003937788,0.0001129782,0.0004929258,0.0009902538,0.0002639932,0.000009463305],"category_scores_gemma":[0.00001384009,0.000289351,0.0001715507,0.00002278482,0.00001670656,0.0002166949,0.0003033676,0.0002266618,0.0007559272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005221611,"about_ca_system_score_gemma":0.0001815012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000111896,"about_ca_topic_score_gemma":0.00003472813,"domain_scores_codex":[0.9982648,0.00001210307,0.0003172232,0.0005849085,0.0005308883,0.0002900046],"domain_scores_gemma":[0.9985902,0.00003309172,0.0003423404,0.0008442224,0.00007992078,0.0001102453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[4.716468e-7,0.000008599299,0.000006135781,0.000002650772,0.00002700543,0.00001228201,0.00001645627,0.000001111002,0.000001419688,0.7009889,0.007140964,0.291794],"study_design_scores_gemma":[0.0002059065,0.0001056068,0.0002610499,0.0001492787,0.0000468688,0.00002928875,0.000002099951,0.0007929189,0.00002561724,0.682487,0.3153385,0.0005559167],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00001608051,0.00008588564,0.09617954,0.0005766519,0.0003601297,0.0002012866,0.0002723759,0.0001934445,0.9021146],"genre_scores_gemma":[0.02479999,0.00002052326,0.008484433,0.00373981,0.0008421043,0.00004529041,0.00007389292,0.00004219125,0.9619518],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3081976,"threshold_uncertainty_score":0.9999559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01183345880876227,"score_gpt":0.249468781012458,"score_spread":0.2376353222036958,"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."}}