{"id":"W4246156179","doi":"10.1109/isit.1993.748404","title":"Quickest Detection of an Abrupt Change in a Random Sequence with Finite Change-Time","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kingston Health Sciences Centre","funders":"","keywords":"Change detection; Sequence (biology); Computer science; Algorithm; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002680908,0.0006287711,0.001191106,0.002351032,0.0004076864,0.001190998,0.001014014,0.001540556,0.001117024],"category_scores_gemma":[0.02440048,0.000448793,0.0004395631,0.0008646168,0.0009123581,0.001598156,0.001446426,0.00156406,0.0002593471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003955424,"about_ca_system_score_gemma":0.0007275386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009794711,"about_ca_topic_score_gemma":0.0009940834,"domain_scores_codex":[0.9985031,0.0002311746,0.00009830057,0.0004301365,0.0006067583,0.0001306543],"domain_scores_gemma":[0.9749396,0.01841114,0.002199909,0.001465867,0.002018726,0.0009645773],"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":[0.004039609,0.0005592713,0.07145303,0.0008710736,0.0004939307,0.001279313,0.0004662561,0.2254992,0.1172894,0.02736048,0.002587776,0.5481006],"study_design_scores_gemma":[0.00006600359,0.0005370643,0.02227514,0.00003393519,0.00008278649,0.001069907,0.00005122322,0.9340279,0.03147142,0.009253659,0.001054869,0.00007609162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3201001,0.0006832423,0.6761307,0.0003407301,0.0001637885,0.0001026146,0.0001689952,0.001155067,0.00115478],"genre_scores_gemma":[0.9277791,0.0001609532,0.07075848,0.0001172611,0.00007631657,0.00004767915,0.0001526041,0.00005571822,0.0008519175],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002680908,"threshold_uncertainty_score":0.01417822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1966922159850862,"score_gpt":0.4335621676582013,"score_spread":0.2368699516731151,"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."}}