{"id":"W4310332067","doi":"10.1177/14604582221142442","title":"Implementation of a machine learning algorithm for automated thematic annotations in avatar: A linear support vector classifier approach","year":2022,"lang":"en","type":"article","venue":"Health Informatics Journal","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut national de psychiatrie légale Philippe-Pinel; Université de Montréal; Institut Universitaire en Santé Mentale de Québec","funders":"Otsuka Canada Pharmaceutical","keywords":"Computer science; Support vector machine; Avatar; Classifier (UML); Machine learning; Artificial intelligence; Linear classifier; Human–computer interaction","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003270921,0.001348024,0.001116401,0.001282505,0.0008367008,0.00154711,0.002225785,0.002004505,0.004561974],"category_scores_gemma":[0.007191956,0.0004616107,0.001005882,0.001040527,0.0003362153,0.001143539,0.001130845,0.003070777,0.00332717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009696176,"about_ca_system_score_gemma":0.001693553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007561255,"about_ca_topic_score_gemma":0.006673567,"domain_scores_codex":[0.9984517,0.0004277449,0.0001915403,0.0004580771,0.0003005652,0.0001703588],"domain_scores_gemma":[0.997115,0.001381901,0.0001330904,0.0001760567,0.001096744,0.00009716731],"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":[0.0003564109,0.0004532948,0.00251768,0.0001448095,0.0001013032,0.0001246938,0.0002647507,0.04283376,0.0118322,0.001726287,0.006233545,0.9334112],"study_design_scores_gemma":[0.00002607979,0.000132205,0.0006016949,0.00002078247,0.00001547093,0.00003763499,0.0001294243,0.9886872,0.006554517,0.002080878,0.00169829,0.00001604074],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03387453,0.0001803834,0.9574029,0.0003466226,0.0001361359,0.0004227503,0.0004146285,0.006364362,0.0008576784],"genre_scores_gemma":[0.1926903,0.0001075552,0.8016651,0.0001626608,0.00007267152,0.0007855709,0.001505161,0.000178106,0.002832886],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007561255,"threshold_uncertainty_score":0.01729852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0680476102787554,"score_gpt":0.4384236603921253,"score_spread":0.3703760501133699,"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."}}