{"id":"W6967980149","doi":"10.5281/zenodo.13839445","title":"Machine Learning in Time Series Anomaly Detection","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Anomaly detection; Series (stratigraphy); Anomaly (physics); Time series; Support vector machine; Computational learning theory","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.003146642,0.0007763355,0.0009320723,0.001348753,0.0003765842,0.001879578,0.0007509133,0.00182108,0.003979788],"category_scores_gemma":[0.006133983,0.0004025422,0.000551308,0.001820451,0.00126947,0.002706408,0.001011293,0.003349491,0.001662743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001032674,"about_ca_system_score_gemma":0.0004082871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005078885,"about_ca_topic_score_gemma":0.0004730156,"domain_scores_codex":[0.9985847,0.0006585983,0.00006773096,0.0002836318,0.0003341608,0.00007116159],"domain_scores_gemma":[0.9972121,0.001862071,0.00008403783,0.0001331818,0.0006275176,0.00008108938],"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":[0.0001266554,0.0000892469,0.0009838524,0.001282692,0.000195269,0.0002921338,0.0002637632,0.02178883,0.004304951,0.3065932,0.1213946,0.5426849],"study_design_scores_gemma":[0.00002387539,0.0001522783,0.001591746,0.0005903037,0.00006441021,0.0004561424,0.0001329671,0.107758,0.004348157,0.5471046,0.3376694,0.0001080928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005752484,0.2820485,0.6530462,0.02207441,0.01595415,0.0000811393,0.0002012571,0.0006517106,0.02019019],"genre_scores_gemma":[0.2634334,0.2483381,0.3326719,0.01033475,0.05346294,0.0004857348,0.000878288,0.0006998003,0.08969499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003979788,"threshold_uncertainty_score":0.01664126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01465720115947581,"score_gpt":0.2140275385583319,"score_spread":0.1993703373988561,"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."}}