{"id":"W2952290980","doi":"10.82308/35405","title":"Intra- and interspecific phenotypic variation in mammals and its effect on biodiversity under climate warming","year":2018,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bergmann's rule; Latitude; Intraspecific competition; Interspecific competition; Ecology; Range (aeronautics); Biodiversity; Biology; Climate change; Phenology; Extinction (optical mineralogy); Variation (astronomy); Global warming; Temperate climate; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005796531,0.0001499453,0.0002148785,0.0006334936,0.0002473352,0.0004709678,0.0002143291,0.0002458746,0.001205807],"category_scores_gemma":[0.00164715,0.0001106454,0.0003681077,0.0005669076,0.0006518069,0.000246825,0.0004224638,0.0002787197,0.0001426325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001446215,"about_ca_system_score_gemma":0.00009667596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001780028,"about_ca_topic_score_gemma":0.003553743,"domain_scores_codex":[0.9995292,0.000209246,0.00002727868,0.0001241412,0.00005966588,0.00005040324],"domain_scores_gemma":[0.9984091,0.0005774059,0.0005218059,0.000194034,0.00009270602,0.0002050271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001333956,0.00003048386,0.9911705,0.00001174587,0.0001810447,0.00007152796,0.000252463,0.0001189147,0.005235374,0.00005322633,0.00003687246,0.002704391],"study_design_scores_gemma":[1.338447e-7,0.00001365605,0.9998572,3.723078e-7,0.000003844789,0.0000154234,0.00003439871,0.0000263499,0.00002659554,0.000008102445,0.00001331733,4.494862e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993157,0.000151079,0.00005018562,0.00001239857,0.000002161692,0.000001352261,0.0000451294,0.000002009702,0.0004198908],"genre_scores_gemma":[0.9998202,0.00003597865,0.00002831581,0.000006592063,0.00000338307,0.000001519744,0.00004053024,0.000001054709,0.00006248246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001780028,"threshold_uncertainty_score":0.004033804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221192627834873,"score_gpt":0.2280921938610796,"score_spread":0.2058802675827308,"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."}}