{"id":"W4365140751","doi":"","title":"Automatic classification of time series of patients with chronic pain","year":2023,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Agence Nationale de la Recherche","keywords":"Series (stratigraphy); Computer science; Chronic pain; Time series; Artificial intelligence; Medicine; Machine learning; Physical therapy; Geology","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":[0.000595468,0.0003782811,0.0005118877,0.001826185,0.0001471075,0.000646584,0.0003085322,0.0006228407,0.001617528],"category_scores_gemma":[0.002533641,0.00007980737,0.0004646053,0.0008716983,0.000128023,0.0003027667,0.0002824447,0.0004526326,0.0005586706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002128378,"about_ca_system_score_gemma":0.0002863677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001709262,"about_ca_topic_score_gemma":0.001737675,"domain_scores_codex":[0.9996756,0.00007621029,0.00004075191,0.00007924088,0.00006814854,0.00006000001],"domain_scores_gemma":[0.998841,0.0005905153,0.0001869481,0.00008951929,0.0002027039,0.00008946023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003904129,0.0006264647,0.4781925,0.0002943414,0.0003057439,0.0006909596,0.0002456527,0.0111518,0.0278553,0.000808234,0.008363443,0.4675614],"study_design_scores_gemma":[0.00009362602,0.0006707548,0.7211233,0.00006706329,0.0002128972,0.001147447,0.0003272229,0.2655772,0.005890021,0.001973764,0.002876662,0.00004014646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9630777,0.001545038,0.02654375,0.0006482485,0.0003501566,0.0000898888,0.00561827,0.0003868118,0.001740129],"genre_scores_gemma":[0.9898216,0.0002624736,0.005414143,0.00004134627,0.0001589727,0.00003689033,0.00368996,0.00001046135,0.0005642154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001826185,"threshold_uncertainty_score":0.005411148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01746475995931278,"score_gpt":0.2054005023251158,"score_spread":0.187935742365803,"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."}}