{"id":"W2162093610","doi":"10.1016/j.ijrobp.2011.06.616","title":"Diffusion Weighted and Dynamic Contrast Enhanced MRI of Prostate in Response to RT","year":2011,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Contrast (vision); Dynamic contrast; Diffusion MRI; Diffusion; Prostate; Dynamic contrast-enhanced MRI; Nuclear medicine; Nuclear magnetic resonance; Radiology; Magnetic resonance imaging; Internal medicine; Artificial intelligence","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":[0.0004594594,0.0003616188,0.0006493033,0.001132148,0.000310171,0.0003898431,0.0005113364,0.001165305,0.003195846],"category_scores_gemma":[0.001651711,0.0002870032,0.0006573203,0.000588686,0.0003395602,0.0003822662,0.0002424722,0.001048265,0.0004251907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003911956,"about_ca_system_score_gemma":0.0003267531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004564519,"about_ca_topic_score_gemma":0.003777116,"domain_scores_codex":[0.9998406,0.00003090014,0.00001416001,0.00001911945,0.00002965042,0.00006545368],"domain_scores_gemma":[0.9995146,0.0001966518,0.00006536909,0.00003139687,0.00007458687,0.0001174067],"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":[0.1017253,0.005232426,0.1662097,0.001502444,0.002009764,0.1089326,0.002751196,0.01082661,0.4803262,0.00087352,0.005819381,0.1137909],"study_design_scores_gemma":[0.0007940568,0.0131791,0.8637221,0.00008545528,0.00116431,0.03923039,0.0008041423,0.007414963,0.06169556,0.0007087901,0.01104382,0.0001573791],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982665,0.003371172,0.001310002,0.00107067,0.0001722264,0.0001358738,0.0008302882,0.00009710608,0.0103477],"genre_scores_gemma":[0.9966,0.0006042761,0.000234783,0.0002308989,0.00009907849,0.00002320546,0.0003814383,0.00001335127,0.001812986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004564519,"threshold_uncertainty_score":0.01069117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01525877879664267,"score_gpt":0.3243019166613756,"score_spread":0.309043137864733,"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."}}