{"id":"W4390344793","doi":"10.1049/htl2.12071","title":"Breamy: An augmented reality mHealth prototype for surgical decision‐making in breast cancer","year":2023,"lang":"en","type":"article","venue":"Healthcare Technology Letters","topic":"Patient-Provider Communication in Healthcare","field":"Health Professions","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Regret; Breast cancer; Anxiety; mHealth; Decision aids; Augmented reality; Clinical decision making; Cancer; Medicine; Computer science; Nursing; Family medicine; Human–computer interaction; Alternative medicine; Psychological intervention; Psychiatry; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001500053,0.0003999304,0.0007949874,0.001543781,0.001544506,0.00001250838,0.001091366,0.00104027,0.0000919518],"category_scores_gemma":[0.0003834482,0.0004029863,0.0001018285,0.003123669,0.0002827992,0.0002533153,0.0004669816,0.002291441,0.0001267524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001939976,"about_ca_system_score_gemma":0.001409032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006215804,"about_ca_topic_score_gemma":0.009692485,"domain_scores_codex":[0.9931188,0.001452103,0.00182846,0.001094018,0.000477599,0.002029049],"domain_scores_gemma":[0.9948156,0.001572023,0.0006804668,0.002000412,0.000581633,0.0003498968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001997923,0.0001740426,0.889073,0.002512667,0.00003218875,0.00006703982,0.003930041,0.00009299968,0.00009375321,0.007576401,0.01268484,0.08176512],"study_design_scores_gemma":[0.0108445,0.0007381417,0.8867594,0.007028397,0.00004077571,0.0001052609,0.01585595,0.008404817,0.0000205522,0.02103406,0.04778104,0.001387093],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5559785,0.0006073174,0.0001514174,0.4330704,0.0009706659,0.006743239,0.0005296979,0.001915166,0.00003357057],"genre_scores_gemma":[0.9680517,0.0005340282,0.002216397,0.01344505,0.000253775,0.01509746,0.0002595505,0.0001203046,0.00002170807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4196254,"threshold_uncertainty_score":0.9998422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.206066686029053,"score_gpt":0.50021737523671,"score_spread":0.2941506892076569,"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."}}