{"id":"W3125989840","doi":"10.1093/jjfinec/nbaa032","title":"Selective Linear Segmentation for Detecting Relevant Parameter Changes","year":2020,"lang":"en","type":"article","venue":"Journal of Financial Econometrics","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université Laval","funders":"","keywords":"Segmentation; Econometrics; Computer science; Economics; Mathematics; Artificial intelligence","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":[0.0004656905,0.00008603094,0.0002649247,0.00034572,0.0001065686,0.00009389866,0.0002927087,0.00004722281,0.000005060926],"category_scores_gemma":[0.002438343,0.00007778147,0.0001601022,0.001346084,0.00000997768,0.0004424764,0.00005434518,0.0001480007,0.000003161414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006989121,"about_ca_system_score_gemma":0.00008644495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002278412,"about_ca_topic_score_gemma":0.000004884206,"domain_scores_codex":[0.9991235,0.00001859572,0.0004147432,0.0001527573,0.0001191266,0.0001712962],"domain_scores_gemma":[0.9985442,0.0002993612,0.0007046443,0.00007178615,0.0002816578,0.00009836397],"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":[0.0001008424,0.00005343016,0.002303339,0.0000672802,0.00008983928,0.00001320608,0.002489895,0.004012645,0.00124237,0.001625959,0.0008288781,0.9871723],"study_design_scores_gemma":[0.002346954,0.007101076,0.009335257,0.00006763713,0.0001513643,0.00007573568,0.0003956357,0.9041497,0.03833616,0.00375654,0.03355903,0.000724942],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09883257,0.0002446199,0.8989033,0.001560246,0.0002867764,0.00009738494,0.000004314171,0.00001226448,0.00005853342],"genre_scores_gemma":[0.7196265,0.00007182577,0.2787296,0.0007607155,0.00078241,0.000003674711,7.551571e-7,0.00000943426,0.00001498657],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9864474,"threshold_uncertainty_score":0.3171836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05229557163017287,"score_gpt":0.2510993745318345,"score_spread":0.1988038029016616,"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."}}