{"id":"W1571885823","doi":"10.1007/11864127_13","title":"Intron Loss Dynamics in Mammals","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Intron; Biology; Genome; Gene; Genetics; Lineage (genetic); Germline; Housekeeping gene; Gene expression","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":[0.0002695752,0.00009735231,0.0002823742,0.0004735834,0.0003073663,0.0007450904,0.0002610745,0.0002916903,0.002280226],"category_scores_gemma":[0.0006090448,0.0002319251,0.0001508737,0.0005983819,0.0003507819,0.0005209622,0.000317838,0.0004254553,0.000638229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003745613,"about_ca_system_score_gemma":0.0001218774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005508935,"about_ca_topic_score_gemma":0.0009504841,"domain_scores_codex":[0.9998715,0.00001321681,0.000007533815,0.00005983438,0.00003083169,0.00001710656],"domain_scores_gemma":[0.9996943,0.0001166732,0.0000795296,0.00003517445,0.00002843154,0.00004586843],"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":[0.0008223411,0.000105982,0.1023379,0.0001812418,0.0001462737,0.00100508,0.001132947,0.03369558,0.6881512,0.06609255,0.002749704,0.1035792],"study_design_scores_gemma":[0.00004575963,0.000436732,0.5840725,0.00006525306,0.0001762118,0.005895053,0.000987486,0.1531893,0.1422229,0.07738933,0.03542098,0.00009855399],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861183,0.001506131,0.004547454,0.0001170579,0.000006613967,0.000002912768,0.0003441997,0.00009023274,0.007267224],"genre_scores_gemma":[0.9951593,0.0004450082,0.001291571,0.00002369872,0.000006493232,0.000004296453,0.0004202622,0.00004081197,0.002608433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002280226,"threshold_uncertainty_score":0.007628143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007299203223643547,"score_gpt":0.2483853952547422,"score_spread":0.2410861920310987,"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."}}