{"id":"W2794682008","doi":"","title":"Using Gene Expression to Predict Tumor Location in Prostate Cancer Tissue","year":2018,"lang":"en","type":"article","venue":"Research in Computational Molecular Biology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Prostate cancer; Cancer; Gene expression; Computer science; Cancer research; Gene; Oncology; Internal medicine; Medicine; Biology; Genetics","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":[0.0002765771,0.000197331,0.0002473194,0.0009067204,0.0001107162,0.0004664711,0.0001951746,0.0003602954,0.0005922229],"category_scores_gemma":[0.0009970588,0.0001261461,0.0002786366,0.0007098487,0.0001845602,0.0002501386,0.000160969,0.0002325114,0.0003568456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000195785,"about_ca_system_score_gemma":0.0002062767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001395546,"about_ca_topic_score_gemma":0.001878963,"domain_scores_codex":[0.9998375,0.00004835109,0.000009000561,0.00004227913,0.00004198585,0.0000208329],"domain_scores_gemma":[0.9996854,0.0001725036,0.00004945017,0.00001964543,0.00005623229,0.0000167858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001115308,0.0002103867,0.367976,0.0001953527,0.0002770568,0.0003799839,0.0001367187,0.05215553,0.3824706,0.0008609802,0.001175069,0.1930471],"study_design_scores_gemma":[0.00004686157,0.0004022577,0.2767494,0.00003202784,0.0003456736,0.0007921675,0.0002762435,0.5879849,0.1278321,0.002418471,0.003071003,0.00004880975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9630706,0.001124592,0.03309704,0.0002550188,0.00003035764,0.00001370216,0.0009172797,0.0002620502,0.001229391],"genre_scores_gemma":[0.9908957,0.0003160767,0.007652266,0.00003794752,0.00002113923,0.00001406465,0.0004591,0.00001367932,0.0005900754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001395546,"threshold_uncertainty_score":0.002774775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05918206320353468,"score_gpt":0.482250000141232,"score_spread":0.4230679369376973,"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."}}