{"id":"W2305653947","doi":"10.1002/cjs.11282","title":"Consistent two‐stage multiple change‐point detection in linear models","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University; York University","funders":"","keywords":"Stage (stratigraphy); Consistency (knowledge bases); Selection (genetic algorithm); Refining (metallurgy); Point (geometry); Change detection; Computer science; Mathematics; Statistics; Algorithm; Applied mathematics; Mathematical optimization; Artificial intelligence; Chemistry; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.03121576,0.001452401,0.00326772,0.003352776,0.001066435,0.002256256,0.005390815,0.002665834,0.002685438],"category_scores_gemma":[0.1055512,0.001955662,0.00373467,0.002424692,0.002598636,0.002694508,0.003881561,0.004580708,0.0006035026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001244705,"about_ca_system_score_gemma":0.003016039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004182637,"about_ca_topic_score_gemma":0.004005544,"domain_scores_codex":[0.9710224,0.0193099,0.001041541,0.004055385,0.003814742,0.0007561168],"domain_scores_gemma":[0.8570676,0.1248392,0.004546783,0.007246256,0.005473208,0.0008270482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001699524,0.0006324594,0.02614537,0.001114287,0.002645453,0.001137384,0.0006235129,0.4821813,0.01355629,0.1269777,0.004987007,0.3382998],"study_design_scores_gemma":[0.00007256115,0.0002243748,0.002336888,0.00002855822,0.0001021035,0.0001036463,0.00002560804,0.956825,0.002818795,0.03644176,0.0009514984,0.00006926343],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004961397,0.00009182747,0.9944917,0.00007480103,0.00001569815,0.00007586551,0.00004611206,0.0001274667,0.0001150641],"genre_scores_gemma":[0.2878754,0.0001464929,0.7093507,0.0001752727,0.00008561624,0.0006057582,0.0005426808,0.0001529769,0.001065014],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03121576,"threshold_uncertainty_score":0.1650867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1931860139358327,"score_gpt":0.3397653221315506,"score_spread":0.1465793081957179,"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."}}