{"id":"W2105260398","doi":"10.1158/1078-0432.ccr-09-2166","title":"Comprehensive MicroRNA Profiling for Head and Neck Squamous Cell Carcinomas","year":2010,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":396,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"","keywords":"microRNA; Head and neck squamous-cell carcinoma; Cancer research; Downregulation and upregulation; Cell cycle; Clonogenic assay; Gene knockdown; Biology; Cell growth; Flow cytometry; Cell; Cell culture; Cancer; Head and neck cancer; Molecular biology; 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":[0.0002945561,0.0002927456,0.0004903479,0.000944377,0.0002747626,0.0004233317,0.0001722191,0.000254329,0.00114589],"category_scores_gemma":[0.0003792289,0.0001253452,0.0003553026,0.0006060745,0.0001279828,0.0001495891,0.0002838111,0.0002172329,0.000467037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002637176,"about_ca_system_score_gemma":0.0004121884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006031984,"about_ca_topic_score_gemma":0.001514845,"domain_scores_codex":[0.9997439,0.00002501732,0.00003316792,0.00007555159,0.00009158253,0.00003088717],"domain_scores_gemma":[0.999862,0.00002791277,0.0000305121,0.00001425156,0.00004758635,0.00001774212],"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":[0.001092633,0.00006050305,0.1229375,0.0006336727,0.0001655569,0.0005437175,0.0001559647,0.000352957,0.8101086,0.00009377485,0.0009129096,0.06294222],"study_design_scores_gemma":[0.00004116555,0.0009171133,0.6423819,0.00009361336,0.0006517239,0.007241034,0.000321848,0.002412781,0.32734,0.0001903058,0.01837236,0.0000361649],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.979412,0.01191444,0.003603379,0.00009683623,0.00003095036,0.0001002173,0.003235763,0.0001507403,0.001455655],"genre_scores_gemma":[0.9814671,0.003225402,0.008594926,0.0001254143,0.00002640298,0.0001243743,0.005083172,0.00003197583,0.001321133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00114589,"threshold_uncertainty_score":0.003833413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1134332804949355,"score_gpt":0.4556207139829654,"score_spread":0.3421874334880299,"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."}}