{"id":"W3177807594","doi":"10.1109/memea52024.2021.9478712","title":"TSEA: An Open Source Python-Based Annotation Tool for Time Series Data","year":2021,"lang":"en","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Python (programming language); Annotation; Graphical user interface; Visualization; Pipeline (software); Data mining; Feature extraction; Artificial intelligence; Time series; Event (particle physics); Noise (video); Noisy data; Machine learning; Pattern recognition (psychology)","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":[0.002745855,0.002197288,0.001113749,0.002593423,0.00104949,0.002241269,0.003184531,0.0009316196,0.04748252],"category_scores_gemma":[0.01049155,0.001054142,0.001877747,0.002389443,0.0008904384,0.00273484,0.003577084,0.003054959,0.02405673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007855038,"about_ca_system_score_gemma":0.003486543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004613298,"about_ca_topic_score_gemma":0.005851857,"domain_scores_codex":[0.9983169,0.0002541681,0.0002526345,0.0004243252,0.0006037743,0.0001483096],"domain_scores_gemma":[0.9956191,0.001823389,0.0004448027,0.0007911632,0.001029507,0.0002919379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001441979,0.0002759471,0.006532003,0.003934715,0.0003913364,0.00118546,0.001283507,0.01666865,0.02711679,0.02110187,0.7247459,0.1953218],"study_design_scores_gemma":[0.0002534958,0.0001427773,0.007951974,0.0005302319,0.0001154513,0.0007762933,0.0001980889,0.1324498,0.03076311,0.04708026,0.779317,0.0004216432],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.002311881,0.0001699182,0.4472062,0.0003870252,0.0003759966,0.0002849016,0.07423865,0.4706689,0.004356469],"genre_scores_gemma":[0.04259049,0.0008350097,0.5419489,0.001407986,0.0003491949,0.004136869,0.2318434,0.1605035,0.01638467],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.04748252,"threshold_uncertainty_score":0.1588448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04869188142570036,"score_gpt":0.2916290802258367,"score_spread":0.2429371988001363,"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."}}