{"id":"W4393093244","doi":"10.1158/1538-7445.am2024-4930","title":"Abstract 4930: Identification of CBX7 and PCDHB18 as novel prognostic biomarkers of cervical cancer: RNA-sequencing and machine learning analysis","year":2024,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Cancer; Identification (biology); Cervical cancer; RNA; Biology; Computational biology; Medicine; Physiology; Oncology; Internal medicine; Bioinformatics; Genetics; Gene; Ecology","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":[0.0007970371,0.0004116842,0.000528453,0.001134736,0.0003046269,0.0007793487,0.0002748189,0.0003875081,0.00261774],"category_scores_gemma":[0.001219954,0.0001418747,0.0004720638,0.0009551852,0.0001797719,0.000210256,0.0002960929,0.0003816872,0.001012814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003891349,"about_ca_system_score_gemma":0.0005553237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00116279,"about_ca_topic_score_gemma":0.00127951,"domain_scores_codex":[0.9997241,0.00003858063,0.00002196906,0.00009739908,0.00008844663,0.00002949755],"domain_scores_gemma":[0.999582,0.0001742369,0.00008509869,0.00002689799,0.0001006015,0.00003127407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001860332,0.0003591575,0.2232995,0.000719968,0.0004509292,0.0006531819,0.0001620013,0.009064404,0.6291683,0.001150009,0.004434928,0.1286772],"study_design_scores_gemma":[0.0001984792,0.0009483366,0.422243,0.0001952377,0.0007208062,0.00167188,0.0002485079,0.2187928,0.333795,0.003063933,0.01802727,0.00009477335],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9533363,0.003660231,0.02583205,0.0003943664,0.00007580895,0.0001684176,0.01329309,0.0005239045,0.002715947],"genre_scores_gemma":[0.9294472,0.001031256,0.04618839,0.0002659678,0.00007751615,0.0002955625,0.02003633,0.0001134206,0.002544317],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.00261774,"threshold_uncertainty_score":0.008757234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04440099942385956,"score_gpt":0.378616168454205,"score_spread":0.3342151690303455,"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."}}