{"id":"W2100398949","doi":"","title":"Prediction and change detection in sequential data for interactive applications","year":2008,"lang":"en","type":"article","venue":"Griffith Research Online (Griffith University, Queensland, Australia)","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Australian Government","keywords":"Computer science; Machine learning; Change detection; Artificial intelligence; Support vector machine; Data mining; Time series","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003918084,0.001520195,0.001834248,0.002564942,0.0008082195,0.001813782,0.002450904,0.002153839,0.001409121],"category_scores_gemma":[0.02219482,0.0005923545,0.0006825871,0.00366987,0.001211988,0.003175368,0.00161854,0.002089642,0.0005020316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006043052,"about_ca_system_score_gemma":0.000944071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003457913,"about_ca_topic_score_gemma":0.003617044,"domain_scores_codex":[0.9975861,0.0006922846,0.0001752778,0.0007320921,0.0006602283,0.0001539743],"domain_scores_gemma":[0.979853,0.01493737,0.002094139,0.001753407,0.0008930195,0.00046907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006441986,0.001138202,0.04342934,0.0004202219,0.0002094147,0.0008353621,0.00069678,0.5125219,0.009165563,0.01328483,0.004603751,0.4130506],"study_design_scores_gemma":[0.00001050209,0.00007861343,0.001811777,0.000006945426,0.00001181684,0.00006739784,0.00005252855,0.987384,0.001576589,0.008282751,0.0007034384,0.00001370747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.120647,0.0005544128,0.8751088,0.0006974384,0.00008739444,0.0001518984,0.0004246795,0.001544665,0.0007836135],"genre_scores_gemma":[0.7600355,0.0002886039,0.2373496,0.0001323914,0.0002710205,0.0002231896,0.000813326,0.0000837191,0.0008027638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003918084,"threshold_uncertainty_score":0.02072102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4241822169354496,"score_gpt":0.4213390490140103,"score_spread":0.002843167921439238,"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."}}