{"id":"W6987495072","doi":"","title":"Synthetic Correlated Diffusion Imaging for Prostate Cancer Detection and Risk Assessment","year":2023,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Blackberry (Canada)","funders":"","keywords":"Prostate cancer; Magnetic resonance imaging; Modality (human–computer interaction); Prostate; Risk assessment; Diffusion MRI; Multiparametric MRI; Cancer","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":[0.001035296,0.000648757,0.0005975563,0.0009473383,0.0002806238,0.001160044,0.0006282494,0.000736986,0.001673763],"category_scores_gemma":[0.003983233,0.0003239923,0.0007690408,0.0009985556,0.0004588527,0.0008072078,0.000839098,0.001028033,0.0007774326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005378856,"about_ca_system_score_gemma":0.0009646473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002917694,"about_ca_topic_score_gemma":0.002835275,"domain_scores_codex":[0.999657,0.0001123169,0.00002012529,0.00006914588,0.0001151339,0.00002629705],"domain_scores_gemma":[0.9989746,0.000503671,0.000149842,0.00009072513,0.0002329271,0.00004836772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003049964,0.0001113865,0.005890914,0.001051809,0.0002417767,0.0004743225,0.0002466857,0.3989718,0.04141698,0.04392397,0.01289869,0.4944667],"study_design_scores_gemma":[0.00001522361,0.00009341595,0.001753809,0.00008998754,0.00006573185,0.0003604802,0.00004945401,0.9558603,0.008735086,0.01834013,0.01457321,0.00006319832],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01628168,0.006525951,0.9701701,0.0009731654,0.0002299005,0.00009453247,0.0005909463,0.001117604,0.004016058],"genre_scores_gemma":[0.3810224,0.01322697,0.5969625,0.0004294187,0.0004523587,0.0003291965,0.001778415,0.0004273136,0.005371465],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002917694,"threshold_uncertainty_score":0.005801439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008171033855852633,"score_gpt":0.2498937246643884,"score_spread":0.2417226908085357,"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."}}