{"id":"W2998769983","doi":"10.1016/s0923-7534(20)31363-6","title":"P3.10 Microrna Profiling in Gastric Cancer","year":2012,"lang":"en","type":"article","venue":"Annals of Oncology","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; Juravinski Cancer Centre","funders":"","keywords":"Medicine; microRNA; Profiling (computer programming); Cancer; Gene expression profiling; Oncology; Cancer research; Computational biology; Internal medicine; Gene expression; Genetics; Gene","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":[0.0003437882,0.0002406027,0.0002567025,0.0006876332,0.000321405,0.0005245256,0.0001666213,0.0005236366,0.001044038],"category_scores_gemma":[0.0004536812,0.0002471037,0.0001981955,0.0004591151,0.0002785906,0.0001851627,0.0002817446,0.0004264544,0.000536785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003052797,"about_ca_system_score_gemma":0.0002859154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007707513,"about_ca_topic_score_gemma":0.001106007,"domain_scores_codex":[0.9998035,0.00003950524,0.00001555673,0.00004233054,0.00005424629,0.00004483763],"domain_scores_gemma":[0.9998829,0.00003496301,0.0000195507,0.00001005553,0.00002785703,0.00002459509],"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":[0.001053369,0.00003210004,0.0133523,0.00007115182,0.00002961922,0.000457954,0.00008317761,0.000184561,0.9743907,0.0002012703,0.000466434,0.009677257],"study_design_scores_gemma":[0.00009277731,0.001023888,0.1963731,0.00003410584,0.0002040985,0.005562611,0.0004541877,0.007638466,0.7747778,0.0007057069,0.01310135,0.00003176368],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896656,0.002369923,0.003021386,0.0001990606,0.00004985937,0.00003423756,0.0009829203,0.0001132099,0.003563774],"genre_scores_gemma":[0.9924793,0.0008023231,0.003673713,0.0001965605,0.0000215047,0.00006466542,0.000865297,0.00004699505,0.001849488],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001044038,"threshold_uncertainty_score":0.003492653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05148537801931091,"score_gpt":0.3691236896915721,"score_spread":0.3176383116722612,"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."}}