{"id":"W2883833412","doi":"10.1101/375246","title":"The Effect of Phylogenetic Uncertainty and Imputation on EDGE Scores","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Amphibian and Reptile Biology","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Utah State University","keywords":"Imputation (statistics); Phylogenetic tree; Missing data; Biology; Phylogenetics; Optimal distinctiveness theory; Endangered species; Evolutionary biology; Supertree; Ecology; Machine learning; Computer science; Habitat","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":[0.02652462,0.0007474319,0.001096893,0.001359266,0.001099024,0.002001939,0.001826022,0.001654867,0.002511834],"category_scores_gemma":[0.09568144,0.0004760188,0.001159685,0.001859007,0.00217142,0.00218529,0.00195224,0.003343568,0.0004174405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001064479,"about_ca_system_score_gemma":0.0007733727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005038472,"about_ca_topic_score_gemma":0.005540856,"domain_scores_codex":[0.9893346,0.007288059,0.0005354252,0.001309582,0.0009743971,0.000557834],"domain_scores_gemma":[0.8667738,0.10823,0.00729915,0.01076085,0.005265085,0.001671093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001026442,0.0001246055,0.1681983,0.0001834328,0.0005400888,0.0002281783,0.0003170274,0.7835901,0.002571799,0.009333037,0.00206413,0.03182292],"study_design_scores_gemma":[0.00006364712,0.0003787344,0.03306359,0.0001346996,0.0002094647,0.0002502013,0.0002586137,0.9395856,0.006761829,0.01710944,0.002091039,0.00009315199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8333768,0.0008162423,0.1581263,0.00121847,0.0001734944,0.00008491006,0.002283382,0.000864173,0.003056325],"genre_scores_gemma":[0.9535723,0.00008708146,0.04370581,0.0002350325,0.00002612068,0.00004610914,0.001672556,0.000112222,0.0005428199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02652462,"threshold_uncertainty_score":0.1402773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006440421229304273,"score_gpt":0.2103091258461988,"score_spread":0.2038687046168946,"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."}}