{"id":"W4280526530","doi":"10.1111/evo.14515","title":"The scaling of diversification rates with age is likely explained by sampling bias","year":2022,"lang":"en","type":"article","venue":"Evolution","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; University of Oregon; Alfred P. Sloan Foundation","keywords":"Biology; Diversification (marketing strategy); Clade; Extant taxon; Sampling bias; Phylogenetic tree; Evolutionary biology; Sampling (signal processing); Identifiability; Econometrics; Statistics; Sample size determination; Genetics; Gene; Mathematics; Computer science","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":[0.0003512811,0.00006512612,0.00008189079,0.00003732604,0.001198792,0.00001337568,0.0001258791,0.00001919118,0.0002289514],"category_scores_gemma":[0.00003596489,0.00004507366,0.00002779741,0.0002197113,0.0001479291,0.00007868762,0.00001346863,0.00009543089,0.00001599312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001329384,"about_ca_system_score_gemma":0.00002583709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001602737,"about_ca_topic_score_gemma":0.005087557,"domain_scores_codex":[0.9992479,0.0001213111,0.0001374539,0.0001373186,0.000208196,0.0001477842],"domain_scores_gemma":[0.9994903,0.0002212859,0.0001197813,0.0001055433,0.00003780563,0.00002530205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000115734,0.00001144339,0.9879079,0.000005344306,0.00003035979,7.142443e-7,0.001067871,0.001668741,0.0001217779,0.0003253825,0.006858775,0.001885883],"study_design_scores_gemma":[0.0002271407,0.000127644,0.9768021,0.000005371119,0.00001757615,0.000004248668,0.004213245,0.005046169,0.00005803925,0.000382477,0.01302928,0.00008674813],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853315,0.006673604,0.002487229,0.00152358,0.0003215688,0.0001874988,0.0001768266,0.00004633855,0.003251881],"genre_scores_gemma":[0.999104,0.00008314438,0.000236413,0.00007212569,0.00002129782,0.000003557354,0.000101982,0.000001348278,0.000376097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01377256,"threshold_uncertainty_score":0.9220261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04777011530256353,"score_gpt":0.2403970433174669,"score_spread":0.1926269280149034,"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."}}