{"id":"W7019246615","doi":"","title":"Guider les thérapeutes dans l'amélioration de la réponse thérapeutique d'un patient à l'aide de l'intelligence artificielle pour la thérapie par Avatar","year":2024,"lang":"fr","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eli Lilly Canada; Fonds de Recherche du Québec - Santé; Institut de Valorisation des Données; Otsuka Canada Pharmaceutical; Eli Lilly and Company","keywords":"Context (archaeology); Poison control; Population; Speech therapy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002555613,0.0006926476,0.0004933218,0.000472399,0.0006878315,0.002602038,0.001310118,0.001818654,0.01303483],"category_scores_gemma":[0.004302091,0.0002485301,0.0006148061,0.00022583,0.001454541,0.001467083,0.001405363,0.002669058,0.005083053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007799708,"about_ca_system_score_gemma":0.002239554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002855994,"about_ca_topic_score_gemma":0.005539221,"domain_scores_codex":[0.9987103,0.0007146099,0.00006525982,0.0001250371,0.0003197342,0.00006499803],"domain_scores_gemma":[0.9988419,0.0005513277,0.0001385131,0.0000955228,0.0002505567,0.0001222868],"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":[0.0004006921,0.0007086311,0.002211694,0.001956505,0.00008801164,0.0009400056,0.003441455,0.002097791,0.01863181,0.03607706,0.03242914,0.9010172],"study_design_scores_gemma":[0.0002973363,0.001642011,0.003746513,0.003503544,0.000184643,0.004462871,0.002268155,0.005880396,0.01394687,0.03594102,0.928008,0.000118644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08119544,0.1768125,0.3276221,0.1056324,0.005192648,0.001745976,0.0006307178,0.00278515,0.2983831],"genre_scores_gemma":[0.3384612,0.1259113,0.3775819,0.02363164,0.001688552,0.002272941,0.0006244752,0.00059283,0.1292351],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01303483,"threshold_uncertainty_score":0.0436058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0135781632798401,"score_gpt":0.2186676688512688,"score_spread":0.2050895055714287,"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."}}