{"id":"W4295082516","doi":"10.1038/s41467-022-32108-3","title":"Thermal adaptation best explains Bergmann’s and Allen’s Rules across ecologically diverse shorebirds","year":2022,"lang":"en","type":"article","venue":"Nature Communications","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Australian Research Council; World Wildlife Fund; Department of Education and Training; Nationaal Regieorgaan Praktijkgericht Onderzoek SIA; MAVA Foundation","keywords":"Foraging; Adaptation (eye); Ecology; Bergmann's rule; Arctic; Predation; Temperate climate; Thermoregulation; Biology; Climate change; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002593548,0.00009702698,0.00009030056,0.00001720004,0.001766189,0.00001906506,0.0008435142,0.0001558201,0.002046494],"category_scores_gemma":[0.00003931592,0.00009267819,0.00003753022,0.00008169407,0.0004192311,0.0001572707,0.002130285,0.0008408841,0.0001472789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001551641,"about_ca_system_score_gemma":0.0000113726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004037112,"about_ca_topic_score_gemma":0.00604395,"domain_scores_codex":[0.9991085,0.0002060189,0.0001325869,0.0002022309,0.0001559401,0.0001947521],"domain_scores_gemma":[0.999085,0.000142808,0.00007067862,0.0006323028,0.00001019344,0.00005899971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003621,0.0009431718,0.9626945,0.000001393673,0.00002340579,0.00001298684,0.007343179,0.001385015,0.0009493211,0.002310585,0.005465365,0.01883488],"study_design_scores_gemma":[0.0002158208,0.0001063434,0.9237314,0.000001049775,0.00002390685,0.0000103475,0.004538988,0.0003918749,0.00001150896,0.0001108317,0.0707241,0.0001337863],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913008,0.0004827224,0.00001434332,0.003019515,0.0001024405,0.0002178287,0.0001090269,0.00005238303,0.004700991],"genre_scores_gemma":[0.994545,0.0001743684,0.00354669,0.0007319212,0.0000109354,0.0001866426,0.0001180681,0.000008809662,0.0006775142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06525873,"threshold_uncertainty_score":0.9995334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0338415951470405,"score_gpt":0.297914925486443,"score_spread":0.2640733303394025,"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."}}