{"id":"W2952772347","doi":"10.1101/030486","title":"Resources for the comprehensive discovery of functional RNA elements","year":2015,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Clinical Research Institute","funders":"National Institutes of Health","keywords":"Computational biology; RNA; Computer science; Business; Chemistry; Biology; Biochemistry; 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":[0.002219495,0.003282978,0.003433371,0.005055466,0.001287425,0.002670479,0.004955389,0.002489183,0.1442085],"category_scores_gemma":[0.004094592,0.001961196,0.001433625,0.007604796,0.0005037844,0.002003616,0.00386901,0.002775911,0.1611124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001171537,"about_ca_system_score_gemma":0.00339674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002612269,"about_ca_topic_score_gemma":0.004358991,"domain_scores_codex":[0.9983075,0.0001524081,0.0002185304,0.0003635531,0.0007134924,0.0002446596],"domain_scores_gemma":[0.9978191,0.0006171926,0.0002717111,0.0005650517,0.0003702582,0.0003567511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001138873,0.0001352274,0.001625954,0.01261657,0.0004647739,0.0007943102,0.0002602209,0.001997538,0.08880644,0.01251041,0.8000376,0.0796121],"study_design_scores_gemma":[0.0004812366,0.00009975149,0.002973754,0.0006638263,0.0002378274,0.0006332478,0.00007083518,0.001532139,0.02836626,0.01165972,0.953169,0.0001124494],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.001584809,0.002546263,0.02082268,0.0003216432,0.0002076092,0.0001705179,0.9340627,0.02451671,0.01576712],"genre_scores_gemma":[0.002868764,0.001260467,0.01443605,0.0001559468,0.0000427636,0.0002843074,0.9741266,0.003732952,0.003091998],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1442085,"threshold_uncertainty_score":0.4824255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02651028880600004,"score_gpt":0.2585934815715265,"score_spread":0.2320831927655264,"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."}}