{"id":"W2467584631","doi":"10.6084/m9.figshare.10637.v1","title":"Panel A: Alternative splicing of Δ33 exon","year":2011,"lang":"en","type":"article","venue":"Figshare","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Exon; RNA splicing; Genetics; Alternative splicing; Computer science; Computational biology; Biology; Gene; RNA","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001236748,0.0006697582,0.0002809188,0.0004872009,0.0005099229,0.0003299146,0.0003161848,0.0007150995,0.06102779],"category_scores_gemma":[0.0002376328,0.0001856044,0.0004063627,0.0003806464,0.0003338958,0.0002344034,0.0002205567,0.0005893253,0.01376829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004481009,"about_ca_system_score_gemma":0.0004155601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001650389,"about_ca_topic_score_gemma":0.002498239,"domain_scores_codex":[0.9996494,0.00002676393,0.00001662178,0.0001601164,0.0000945123,0.00005270505],"domain_scores_gemma":[0.9997062,0.0000738657,0.00006190834,0.0000530057,0.0000479345,0.00005718469],"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":[0.0004793725,0.0001011762,0.001553733,0.0001896723,0.00001969929,0.001314329,0.00007956696,0.0001447592,0.9654582,0.001993067,0.01508141,0.0135851],"study_design_scores_gemma":[0.0001864359,0.0006238685,0.09213167,0.0001707985,0.00007596259,0.01100614,0.0005008819,0.001168954,0.7054369,0.001858201,0.1867858,0.00005434764],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.7998866,0.001443049,0.03413489,0.001966505,0.0007102233,0.0008051869,0.05669698,0.001618983,0.1027377],"genre_scores_gemma":[0.7721962,0.001597263,0.04306051,0.002404907,0.0001467863,0.0005490324,0.09958994,0.0006105915,0.07984467],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.06102779,"threshold_uncertainty_score":0.2041583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1206479502337219,"score_gpt":0.2934945488019124,"score_spread":0.1728465985681905,"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."}}