{"id":"W4415668036","doi":"10.1093/jcag/gwaf026","title":"Exploring a novel voice-guided artificial intelligence platform for real-time colonoscopy documentation: a pilot study","year":2025,"lang":"en","type":"article","venue":"Journal of the Canadian Association of Gastroenterology","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vale (Canada); Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"Université de Montréal","keywords":"Colonoscopy; Documentation; Completeness (order theory); Endoscopy; Applications of artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.005267596,0.0007774571,0.0004399316,0.0005960543,0.0003512443,0.001265839,0.001486423,0.0008601549,0.003635023],"category_scores_gemma":[0.01171848,0.0002749502,0.0006082495,0.0003018743,0.0005583783,0.001071764,0.001204776,0.0006087152,0.001136002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005527802,"about_ca_system_score_gemma":0.001201276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001861158,"about_ca_topic_score_gemma":0.001861531,"domain_scores_codex":[0.9977524,0.00123148,0.0001821267,0.0003084121,0.0003383238,0.0001873724],"domain_scores_gemma":[0.9908494,0.005437718,0.0004950647,0.0007144286,0.001791566,0.000711777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.006573954,0.01683348,0.056437,0.00275342,0.0003575564,0.004982335,0.01444353,0.009685018,0.1596488,0.001003472,0.006525841,0.7207557],"study_design_scores_gemma":[0.00731796,0.1352236,0.2260367,0.0008250892,0.001594823,0.008559046,0.01348947,0.2958712,0.2512253,0.002112944,0.05691799,0.0008259576],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.934888,0.0001757092,0.05745982,0.000311088,0.0000723269,0.003222236,0.0004278188,0.002047291,0.001395663],"genre_scores_gemma":[0.8077243,0.0002363966,0.1846828,0.0004257376,0.00007977256,0.003096155,0.0009214269,0.0002227592,0.002610645],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005267596,"threshold_uncertainty_score":0.02785802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09137850321255184,"score_gpt":0.3246584082924811,"score_spread":0.2332799050799293,"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."}}