{"id":"W3081554387","doi":"","title":"Effects of body mass, climate, geography, and census area on population density of terrestrial mammals","year":2000,"lang":"en","type":"article","venue":"Geologia Sudetica","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Population density; Biome; Population; Geography; Ecology; Mammal; Density dependence; Temperate climate; Bergmann's rule; Census; Physical geography; Biology; Demography; Ecosystem; Latitude","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":[0.002132531,0.0002980875,0.0003525176,0.0007427478,0.0002481861,0.0005147682,0.0002911529,0.0002503557,0.00175214],"category_scores_gemma":[0.01064741,0.0001749921,0.0005332398,0.0008171176,0.0003710484,0.0005257436,0.0004016648,0.0003308327,0.0002642436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001820388,"about_ca_system_score_gemma":0.000185277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00341054,"about_ca_topic_score_gemma":0.004920593,"domain_scores_codex":[0.9984243,0.001054312,0.000094799,0.0002187969,0.0001434856,0.00006430506],"domain_scores_gemma":[0.9884753,0.008045003,0.002119031,0.0005155811,0.0004501426,0.0003948885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008061867,0.00001424002,0.9969139,0.00001234148,0.0001805453,0.00003695063,0.0000255828,0.0002342362,0.0001611123,0.00002168442,0.00002474279,0.002294053],"study_design_scores_gemma":[0.000001417948,0.00005559685,0.9989185,0.000003593228,0.00004261645,0.00005861338,0.00003698935,0.000737363,0.0000520783,0.00003598281,0.00005504144,0.000002243264],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970937,0.001291905,0.000735603,0.00006016464,0.000008985376,0.000006746192,0.0002302698,0.00001077541,0.0005618812],"genre_scores_gemma":[0.9991461,0.0001888029,0.0003280907,0.0000158121,0.000014443,0.000005700325,0.0001656381,0.000004199214,0.0001313132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00341054,"threshold_uncertainty_score":0.01127803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005009906585357439,"score_gpt":0.1956132241809201,"score_spread":0.1906033175955626,"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."}}