{"id":"W2948504187","doi":"10.1038/s41374-019-0265-2","title":"Reliable identification of prostate cancer using mass spectrometry metabolomic imaging in needle core biopsies","year":2019,"lang":"en","type":"article","venue":"Laboratory Investigation","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Southeastern Ontario Academic Medical Organization; Canadian Institutes of Health Research; Queen's University; Imperial College London","keywords":"Prostate cancer; Metabolomics; Prostate; Cancer; Medicine; Biochemical recurrence; Oncology; Computational biology; Prostatectomy; Pathology; Internal medicine; Bioinformatics; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001112972,0.0005424065,0.0004814849,0.001427087,0.0003064177,0.001032856,0.0004460736,0.0008535713,0.0006562299],"category_scores_gemma":[0.002523457,0.000293126,0.0002547124,0.0007317527,0.0003513766,0.0004364103,0.0004589378,0.0004921216,0.000385764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002431192,"about_ca_system_score_gemma":0.0003658496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001164262,"about_ca_topic_score_gemma":0.002379864,"domain_scores_codex":[0.9990086,0.0002767787,0.00006057027,0.0001759559,0.0003934888,0.00008458841],"domain_scores_gemma":[0.9992164,0.0002755128,0.0001416691,0.00007420335,0.0002330875,0.00005905905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001579426,0.0001422967,0.1772761,0.000286511,0.0001752789,0.0005974672,0.0001759865,0.0006345574,0.7591549,0.0004513045,0.0007646228,0.05876147],"study_design_scores_gemma":[0.00003783391,0.0005055341,0.4667701,0.000119145,0.0003356129,0.003885972,0.0004484551,0.0147455,0.5078008,0.001131117,0.004166265,0.00005372951],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.915302,0.01791316,0.05915935,0.0008593673,0.0001440612,0.0001908603,0.001442359,0.0004757968,0.004513158],"genre_scores_gemma":[0.9713913,0.002100715,0.02452941,0.0004318021,0.00008310816,0.00006009102,0.0004912102,0.00004610511,0.0008661425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001427087,"threshold_uncertainty_score":0.005886018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01155030004841393,"score_gpt":0.2552876140886262,"score_spread":0.2437373140402123,"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."}}