{"id":"W4249137255","doi":"10.2174/978160805184711001010001","title":"miRNA Biology","year":2010,"lang":"en","type":"book-chapter","venue":"BENTHAM SCIENCE PUBLISHERS eBooks","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"","keywords":"microRNA; Section (typography); Biology; Function (biology); Transcription (linguistics); Computational biology; Action (physics); Psychological repression; Gene; Genetics; Gene expression; Computer science; Philosophy; Linguistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005058797,0.0003712236,0.0002376927,0.0003066404,0.0002633267,0.0004180473,0.001171289,0.0007600393,0.0003380387],"category_scores_gemma":[0.0001410011,0.0003655367,0.0001983644,0.00003842233,0.001949921,0.00002341016,0.0005103208,0.0003707264,0.00006074973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000656194,"about_ca_system_score_gemma":0.000939306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001120937,"about_ca_topic_score_gemma":0.00003114775,"domain_scores_codex":[0.9977074,0.00001402306,0.0003241762,0.001051879,0.0003847187,0.0005178367],"domain_scores_gemma":[0.9979461,0.000008507062,0.0002898134,0.001073814,0.0003544525,0.0003273172],"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":[0.00001760306,0.00001128685,0.00004465454,0.00001326997,0.00003483459,0.000002748534,0.00002009856,7.226318e-7,0.9664659,0.01728758,0.00733252,0.00876877],"study_design_scores_gemma":[0.0002339149,0.00009052805,0.0001861045,0.00002325333,0.00003190394,0.00002015043,0.000006372609,0.000004554084,0.07705256,0.006756465,0.9150888,0.0005054233],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01202194,0.0002950632,0.000147393,0.0001177744,0.00137395,0.0004353824,0.00005982384,0.00004757378,0.9855011],"genre_scores_gemma":[0.2013871,0.00001333163,0.002067075,0.0006523525,0.001435297,0.00005125056,0.0006680855,0.0001558299,0.7935696],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9077563,"threshold_uncertainty_score":0.9998797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01211251284844879,"score_gpt":0.2476150101764228,"score_spread":0.235502497327974,"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."}}