{"id":"W3134456376","doi":"10.1016/j.jmir.2021.02.001","title":"RE: Perceptions of Canadian radiation oncologists, radiation physicists, radiation therapists and radiation trainees about the impact of artificial intelligence in radiation oncology – National survey","year":2021,"lang":"en","type":"letter","venue":"Journal of medical imaging and radiation sciences","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Radiation oncology; Radiation Therapist; Medical physicist; Medicine; Scopus; Coronavirus disease 2019 (COVID-19); Medical physics; Context (archaeology); Medical education; Psychology; Radiation therapy; MEDLINE; Radiology; Pathology; Political science; History","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002386629,0.0002328606,0.0002845646,0.0007262093,0.006613168,0.001792408,0.001210466,0.006227938,0.008864532],"category_scores_gemma":[0.01280484,0.0004129176,0.0004195051,0.001385989,0.001084762,0.0008054271,0.0009517315,0.003566015,0.00154549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02610467,"about_ca_system_score_gemma":0.0533261,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.9635316,"about_ca_topic_score_gemma":0.9821483,"domain_scores_codex":[0.9978017,0.0002204702,0.0001901595,0.000112005,0.0008306006,0.0008450407],"domain_scores_gemma":[0.9831902,0.002577716,0.001210322,0.0002545768,0.007486577,0.005280554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001351432,0.00008234687,0.1598766,0.00007934408,0.00002082849,0.001161585,0.003969333,0.0001322947,0.0003890957,0.0005540419,0.8180484,0.015551],"study_design_scores_gemma":[0.00008328002,0.0001128278,0.5931199,0.0003988382,0.0000480537,0.001266896,0.05428533,0.0006262073,0.0005401136,0.0005143339,0.3488355,0.0001687684],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.1387032,0.0008915795,0.00009400693,0.8162879,0.002501504,0.0001139027,0.005652891,0.00006204248,0.03569289],"genre_scores_gemma":[0.4502143,0.001828012,0.0004120956,0.4654523,0.001501353,0.000170189,0.002893995,0.00007744649,0.07745019],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9635316,"threshold_uncertainty_score":0.1894035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1613574883674754,"score_gpt":0.4812883363254887,"score_spread":0.3199308479580133,"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."}}