{"id":"W1983705148","doi":"10.1002/jmri.20014","title":"Usefulness of contrast kinetics for predicting and monitoring tissue changes in muscle following thermal therapy in long survival studies","year":2004,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Ultrasound and Hyperthermia Applications","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women's College Hospital; University of Toronto; Sunnybrook Health Science Centre","funders":"National Cancer Institute","keywords":"Histopathology; Magnetic resonance imaging; Medicine; Kinetics; Lesion; Nuclear medicine; Ultrasound; Histology; Inflammation; Pathology; Radiology; Internal medicine","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":[0.001173063,0.0005569835,0.0003468663,0.0006476578,0.0001117752,0.0004647009,0.0002089616,0.0005578809,0.00052119],"category_scores_gemma":[0.001515744,0.0002054591,0.000156502,0.0001809503,0.0003940696,0.0006840446,0.0002159039,0.0002920982,0.0002312076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002034064,"about_ca_system_score_gemma":0.0002084857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003537381,"about_ca_topic_score_gemma":0.000450012,"domain_scores_codex":[0.9998245,0.0000583967,0.00001776381,0.00004133398,0.00003745599,0.00002066945],"domain_scores_gemma":[0.9991033,0.0002521085,0.0003850128,0.00007463807,0.0001281604,0.0000567947],"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":[0.001194542,0.00005716596,0.02617835,0.0001725818,0.00002699783,0.0001383298,0.00005536516,0.0005139018,0.9557334,0.00004302908,0.00002781035,0.01585845],"study_design_scores_gemma":[0.00003136886,0.004440845,0.1526944,0.00007513418,0.0002640849,0.0020383,0.0001759292,0.009147898,0.8290631,0.0001649792,0.001864267,0.00003980213],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9753919,0.007499679,0.01608487,0.00004606185,0.00001229846,0.00006897296,0.0001162895,0.0001295101,0.0006504283],"genre_scores_gemma":[0.9892832,0.002538395,0.007523345,0.00003066515,0.00001151618,0.00005315514,0.0001347915,0.00002113799,0.0004037654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001173063,"threshold_uncertainty_score":0.00620383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02102789331972063,"score_gpt":0.2688535194606636,"score_spread":0.247825626140943,"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."}}