{"id":"W2107808362","doi":"10.1080/10635150290102429","title":"Identifiability of Parameters in MCMC Bayesian Inference of Phylogeny","year":2002,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":200,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Human Genome Research Institute; National Institutes of Health","keywords":"Markov chain Monte Carlo; Bayesian inference; Bayesian probability; Inference; Identifiability; Bayes' theorem; Posterior probability; Context (archaeology); Computer science; Algorithm; Biology; Artificial intelligence; Machine learning","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":[0.02562473,0.001780472,0.002634651,0.00501748,0.002399386,0.004540632,0.003088127,0.005537638,0.003379583],"category_scores_gemma":[0.1843971,0.002804516,0.001748408,0.006319902,0.007558879,0.007747769,0.004500723,0.008271731,0.001141201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002809253,"about_ca_system_score_gemma":0.004056424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006781808,"about_ca_topic_score_gemma":0.004745488,"domain_scores_codex":[0.9812399,0.01226339,0.001078171,0.001830666,0.003035107,0.0005528311],"domain_scores_gemma":[0.9041131,0.07942906,0.00435052,0.009116377,0.002320225,0.0006706912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009370944,0.000038711,0.004600822,0.0003548504,0.0002250596,0.0003703874,0.0009817093,0.347697,0.001244797,0.5692375,0.003143155,0.07201222],"study_design_scores_gemma":[0.00002006176,0.000009103945,0.0004523405,0.0001076492,0.00003272418,0.0001294234,0.00005011598,0.3796043,0.000524578,0.6159366,0.003066038,0.00006704143],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00319374,0.0005935662,0.9945613,0.0004433014,0.00003727726,0.00003235846,0.0001006887,0.0002057144,0.0008321773],"genre_scores_gemma":[0.2226987,0.002725579,0.7696294,0.0007833817,0.0003420631,0.0006218861,0.0009055485,0.0006851582,0.001608373],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02562473,"threshold_uncertainty_score":0.1355182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02282316107560644,"score_gpt":0.2580838828755768,"score_spread":0.2352607217999703,"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."}}