{"id":"W2981503473","doi":"10.1101/816603","title":"The latitudinal gradient in hand-wing-index: global patterns and predictors of wing morphology in birds","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Ontario Museum","funders":"Clarendon Fund; Natural Sciences and Engineering Research Council of Canada; Natural Environment Research Council; US-UK Fulbright Commission; Sight Research UK","keywords":"Biological dispersal; Ecology; Geography; Macroecology; Latitude; Habitat; Proxy (statistics); Biology; Biogeography; Demography; Statistics; Population","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003938826,0.0001653287,0.0001707648,0.0007828719,0.0001156492,0.000422048,0.0001113967,0.0001417248,0.001812026],"category_scores_gemma":[0.0007656224,0.00008994569,0.0001825173,0.001148287,0.0002140808,0.0001962449,0.0003694781,0.0001750939,0.0004457409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007258168,"about_ca_system_score_gemma":0.00007105991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002879751,"about_ca_topic_score_gemma":0.00492099,"domain_scores_codex":[0.9998459,0.00003703655,0.00001044831,0.00006911148,0.00001791973,0.00001961328],"domain_scores_gemma":[0.9991724,0.0001659219,0.0003275935,0.0001323352,0.00009319289,0.0001086339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003223377,0.000006057759,0.9952422,0.000009220223,0.00005614346,0.000009768447,0.00003654478,0.0002904159,0.001411887,0.00003011231,0.0002900171,0.002585484],"study_design_scores_gemma":[6.486923e-7,0.000003569683,0.999507,0.000001418377,0.000004509271,0.00001238764,0.00002545483,0.000240259,0.00006839465,0.00002107533,0.0001140679,0.000001239618],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996982,0.0001111288,0.0005083174,0.0000259133,0.000003745286,0.000001616918,0.002009887,0.00001604051,0.0003412676],"genre_scores_gemma":[0.9969361,0.000045131,0.000369857,0.000008101627,0.000006616001,0.000002883159,0.002426446,0.00001089829,0.0001939742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002879751,"threshold_uncertainty_score":0.006061852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00991969507292427,"score_gpt":0.2147705330700548,"score_spread":0.2048508379971306,"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."}}