{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009586187,0.0001932568,0.0002178053,0.0002029602,0.0001119775,0.000302541,0.000244521,0.0001915116,0.0005337671],"category_scores_gemma":[0.0008821498,0.0001566412,0.0001170126,0.0001116595,0.0001848711,0.0002846628,0.0002404365,0.0001756076,0.000195794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003062101,"about_ca_system_score_gemma":0.0003199129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000930967,"about_ca_topic_score_gemma":0.00103226,"domain_scores_codex":[0.9998554,0.00004299028,0.000006720342,0.00003279686,0.00003896217,0.00002310238],"domain_scores_gemma":[0.9996725,0.0000520513,0.00007548182,0.00005386978,0.00009854699,0.00004759218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.006149617,0.001161494,0.2038382,0.0002667764,0.0001446711,0.0002589686,0.0004424314,0.01123672,0.726907,0.000309792,0.0007304882,0.04855387],"study_design_scores_gemma":[0.0003992025,0.02561792,0.5630912,0.0000247584,0.0003126019,0.002265673,0.0003220236,0.07363215,0.3305332,0.0002587772,0.003466177,0.0000764026],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971663,0.00008229033,0.002400361,0.00001482913,0.000001868733,0.00002322412,0.00006765985,0.00005165672,0.000191722],"genre_scores_gemma":[0.9951807,0.00003844564,0.004255003,0.00001562717,0.000003567649,0.0000250152,0.0002470412,0.00001363053,0.0002209434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009586187,"threshold_uncertainty_score":0.005069733,"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."}}