{"id":"W2989662188","doi":"10.3389/fonc.2019.01305","title":"Expanding the Transcriptome of Head and Neck Squamous Cell Carcinoma Through Novel MicroRNA Discovery","year":2019,"lang":"en","type":"article","venue":"Frontiers in Oncology","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Dalhousie University; Occupational Cancer Research Centre","funders":"BC Cancer Foundation; Canadian Institutes of Health Research; Fonds de Recherche en Santé Respiratoire; Fundação de Amparo à Pesquisa do Estado de São Paulo; Fondation du Souffle","keywords":"Head and neck squamous-cell carcinoma; microRNA; Biology; Computational biology; In silico; Transcriptome; Context (archaeology); Head and neck cancer; Bioinformatics; Cancer; Gene; Gene expression; Genetics","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":[0.0001229023,0.0001250097,0.0002233236,0.00004418393,0.00003058041,0.000009295173,0.0001711923,0.0001847939,0.000007035841],"category_scores_gemma":[0.00001680755,0.0001040667,0.00006938252,0.00008039206,0.0001486608,0.00001153579,0.00006648691,0.00009480447,0.000001243035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000584105,"about_ca_system_score_gemma":0.00009909608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000580202,"about_ca_topic_score_gemma":0.00002592709,"domain_scores_codex":[0.99914,0.00006767596,0.0002324252,0.00028225,0.00006649338,0.0002112149],"domain_scores_gemma":[0.9995486,0.00002036561,0.0001094729,0.0002696908,0.00002323649,0.00002863567],"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":[0.0002395149,0.000112795,0.1145306,0.00005899232,0.00001308265,0.000001802001,0.0004044552,0.00006607317,0.8822266,0.00003189453,0.001997273,0.0003169431],"study_design_scores_gemma":[0.007239108,0.001274184,0.234045,0.00003179327,0.00007366868,0.00004191201,0.001911715,0.0002295891,0.71152,0.000352949,0.04285121,0.0004289324],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885799,0.004248972,0.004951481,0.0001697512,0.0006483771,0.0003266999,0.00002858797,0.000003301021,0.001042939],"genre_scores_gemma":[0.9961302,0.00008310259,0.003138072,0.0001797034,0.00007130436,0.00001366397,0.00003977549,0.00001747855,0.0003266746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1707066,"threshold_uncertainty_score":0.4243716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01008225214279512,"score_gpt":0.2539558359170936,"score_spread":0.2438735837742985,"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."}}