{"id":"W2023617697","doi":"10.1158/1535-7163.targ-11-b25","title":"Abstract B25: Emerging role of heterogeneous ribonucleoproteins (hnRNPs) as early predictive marker and prognosticator for head and neck oral squamous cell carcinoma.","year":2011,"lang":"en","type":"article","venue":"Molecular Cancer Therapeutics","topic":"RNA modifications and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Biomarker; Immunohistochemistry; Heterogeneous ribonucleoprotein particle; Ribonucleoprotein; Malignancy; Biology; Pathology; Cancer research; Head and neck squamous-cell carcinoma; Tissue microarray; Cancer; Medicine; RNA; Head and neck cancer; Biochemistry","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":[0.0006851971,0.0003158109,0.00022634,0.0005263246,0.0001223876,0.0003873193,0.000217385,0.0002456609,0.001362396],"category_scores_gemma":[0.0003750837,0.0001099252,0.0001365601,0.0002912329,0.0002686862,0.0001478442,0.0001269473,0.0002430256,0.0004669408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002628035,"about_ca_system_score_gemma":0.0002189067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001147416,"about_ca_topic_score_gemma":0.000916732,"domain_scores_codex":[0.9998922,0.00002224975,0.00001002996,0.00003262779,0.00003207303,0.00001078145],"domain_scores_gemma":[0.9997872,0.000059404,0.00005576489,0.00001490725,0.0000501379,0.00003258096],"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":[0.002910506,0.0002552001,0.2873907,0.0005384764,0.000172243,0.001025774,0.00007827325,0.0004732358,0.5996739,0.000207144,0.001105501,0.1061691],"study_design_scores_gemma":[0.00005233317,0.001531948,0.8455411,0.00006949143,0.0002663076,0.003438311,0.0001375126,0.002649249,0.1407392,0.0004018867,0.005151843,0.00002090864],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758523,0.01893895,0.002449676,0.0003374387,0.00004404987,0.00003800416,0.0008664923,0.00008844139,0.001384639],"genre_scores_gemma":[0.9910523,0.003353204,0.00304173,0.00008203161,0.00005825628,0.00002338142,0.001102815,0.000009673132,0.001276491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001362396,"threshold_uncertainty_score":0.00455761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01795582181297666,"score_gpt":0.258876544099643,"score_spread":0.2409207222866663,"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."}}