{"id":"W4364359356","doi":"","title":"Clustering de séries chronologiques de patients souffrant de douleurs chroniques","year":2023,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Healthcare Systems and Practices","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Cluster analysis; Computer science; 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":[0.00130419,0.0004060368,0.0007251598,0.00759527,0.0006776959,0.001527413,0.000931881,0.0009265093,0.006125294],"category_scores_gemma":[0.01739559,0.0002572317,0.001244133,0.005230057,0.0004025669,0.0005634994,0.0005550393,0.0006377751,0.001399786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008723414,"about_ca_system_score_gemma":0.001139302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009338993,"about_ca_topic_score_gemma":0.008610169,"domain_scores_codex":[0.9978942,0.0003965812,0.0003103086,0.0005481419,0.0004846792,0.0003661224],"domain_scores_gemma":[0.9823924,0.008377446,0.003511932,0.001415923,0.00289943,0.001402997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001698761,0.000136562,0.9165089,0.0005013361,0.0005703242,0.0007390436,0.001286421,0.007507287,0.004013633,0.002535114,0.01003249,0.05447026],"study_design_scores_gemma":[0.0001024211,0.0004564934,0.9497095,0.0001515199,0.0002906296,0.003967713,0.002315139,0.02153807,0.002253351,0.00315006,0.0159962,0.00006909091],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9582729,0.001828018,0.008858058,0.0005101086,0.00012297,0.0002141274,0.02674398,0.0004198925,0.003029969],"genre_scores_gemma":[0.9601376,0.0007042441,0.00641258,0.00008431412,0.0001476877,0.0002019156,0.0296487,0.00007849338,0.002584577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009338993,"threshold_uncertainty_score":0.02049118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06601120879365602,"score_gpt":0.3663799917549325,"score_spread":0.3003687829612765,"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."}}