{"id":"W4385213763","doi":"10.1016/j.ctro.2023.100666","title":"Longitudinal diffusion and volumetric kinetics of head and neck cancer magnetic resonance on a 1.5 T MR-linear accelerator hybrid system: A prospective R-IDEAL stage 2a imaging biomarker characterization/pre-qualification study","year":2023,"lang":"en","type":"article","venue":"Clinical and Translational Radiation Oncology","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Division of Civil, Mechanical and Manufacturing Innovation; Ministry of Higher Education; National Institute of Biomedical Imaging and Bioengineering; National Institute of Dental and Craniofacial Research; University of Texas MD Anderson Cancer Center; Elekta; Radiation Oncology Institute; National Science Foundation; Israel National Road Safety Authority; Patient-Centered Outcomes Research Institute; National Cancer Institute; National Institutes of Health","keywords":"Magnetic resonance imaging; Medicine; Stage (stratigraphy); Head and neck cancer; Head and neck; Nuclear medicine; Diffusion MRI; Radiology; Nuclear magnetic resonance; Radiation therapy; Surgery; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0006010968,0.0001671732,0.0004798837,0.0002992283,0.0001158279,0.00001991197,0.00004690024,0.0001042635,0.00005162492],"category_scores_gemma":[0.0001920394,0.0001555717,0.00004854261,0.0005561154,0.0002251602,0.0001029717,0.00002602797,0.0002080399,0.000003973535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006963559,"about_ca_system_score_gemma":0.0001364611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008633437,"about_ca_topic_score_gemma":0.00005828877,"domain_scores_codex":[0.9979107,0.000251979,0.0008109506,0.0005396797,0.000312966,0.0001737398],"domain_scores_gemma":[0.9981658,0.001044763,0.0002670737,0.0001474344,0.0002222962,0.0001525611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009156071,0.0005642063,0.8751346,0.0001539948,0.00004141376,0.00001452567,0.0003707495,0.00001169909,0.0005887892,0.0001973993,0.00006670734,0.1219402],"study_design_scores_gemma":[0.005658069,0.001427488,0.9556127,0.0001231598,0.0001532789,0.00001257281,0.00008921087,0.03338202,0.0000576173,0.00003232823,0.003325914,0.0001256269],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925026,0.001627577,0.0002880402,0.003694069,0.0002475893,0.00127189,0.0002660239,0.00005317423,0.00004899653],"genre_scores_gemma":[0.9949625,0.003917471,0.0002255184,0.0001709368,0.0002333348,0.0002132933,0.0001563002,0.00002180291,0.0000988817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1218146,"threshold_uncertainty_score":0.6344029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07193270830227526,"score_gpt":0.4140203368205925,"score_spread":0.3420876285183172,"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."}}