{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003660538,0.0001443877,0.0002193947,0.0002130714,0.00004207189,0.0000216484,0.0001149731,0.0000712258,0.00001995924],"category_scores_gemma":[0.00007927551,0.0001492827,0.00003722458,0.0006634943,0.0000988101,0.00002550686,0.00004664614,0.00008486274,0.000005474902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004968253,"about_ca_system_score_gemma":0.0001538762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001103904,"about_ca_topic_score_gemma":0.00002132956,"domain_scores_codex":[0.9988983,0.0000432063,0.000390067,0.0003265516,0.0001387627,0.0002031238],"domain_scores_gemma":[0.9991665,0.000007512505,0.0003087678,0.0002840064,0.0001931749,0.000039989],"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":[0.00001822793,0.000009442968,0.3057998,0.00003713395,0.00001837499,2.667894e-7,0.00007357582,0.0005326099,0.6930616,0.0003555891,0.00006897171,0.0000244152],"study_design_scores_gemma":[0.0004006896,0.0000296505,0.06949321,0.00002880868,0.00002763772,6.550575e-7,0.0003731507,0.001351014,0.9266171,0.0006750372,0.000829901,0.0001731234],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950743,0.003922643,0.00009098782,0.00009549202,0.0003424336,0.0002792041,0.00007865153,0.00001062756,0.0001056126],"genre_scores_gemma":[0.9962261,0.0007716494,0.002497026,0.0001096839,0.0000720079,0.00002366671,0.00007318649,0.00002270163,0.0002040016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2363066,"threshold_uncertainty_score":0.6087571,"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."}}