{"id":"W2111386604","doi":"10.1093/molbev/msv099","title":"Relaxing the Molecular Clock to Different Degrees for Different Substitution Types","year":2015,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Biology; Substitution (logic); Divergence (linguistics); Molecular clock; CpG site; Evolutionary biology; Context (archaeology); Genetics; Molecular evolution; Variation (astronomy); Locus (genetics); Computational biology; Sequence (biology); Phylogenetics; Gene; Computer science; DNA methylation","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001591443,0.0001792966,0.0001530459,0.00003658457,0.0001619702,0.00001587306,0.0001325461,0.0001545362,6.099217e-7],"category_scores_gemma":[0.0001330286,0.0001229852,0.00007810992,0.00004800079,0.000115879,7.911034e-7,0.00015324,0.00005923625,0.00000281645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002878995,"about_ca_system_score_gemma":0.00002700502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001984972,"about_ca_topic_score_gemma":0.00005508059,"domain_scores_codex":[0.9990961,0.00008825667,0.0001548975,0.0003449334,0.00005902948,0.000256815],"domain_scores_gemma":[0.999495,0.00001454551,0.00004931041,0.0002416454,0.0000992736,0.0001001781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001556174,0.000032557,0.0153399,0.0000086188,0.0001103906,8.412898e-7,0.00006743817,0.000780988,0.9428639,0.03963656,0.0002534938,0.0007496938],"study_design_scores_gemma":[0.003775791,0.004538727,0.2022676,0.00005460444,0.0004199606,0.00007903759,0.0004632747,0.002186789,0.6529729,0.04592537,0.08583529,0.001480552],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8803557,0.008741328,0.1095403,0.0006253596,0.0002576904,0.0003633675,0.00001754769,0.00000592887,0.00009273172],"genre_scores_gemma":[0.9985514,0.00009735194,0.0007103129,0.0002765766,0.0001186262,0.0001120371,0.00006500811,0.00001428396,0.00005442696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2898909,"threshold_uncertainty_score":0.5015191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01588462662155291,"score_gpt":0.2610559911538858,"score_spread":0.2451713645323329,"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."}}