{"id":"W6929724551","doi":"10.5061/dryad.x69p8czk5","title":"Predicting potential distributions of large carnivores in Kenya: An occupancy study to guide conservation","year":2022,"lang":"en","type":"dataset","venue":"Socio-Environmental Systems Modeling","topic":"Regulation of Appetite and Obesity","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Construction Owners Association of Alberta","funders":"","keywords":"Carnivore; Occupancy; IUCN Red List; Range (aeronautics); Wildlife; Camera trap; Distribution (mathematics); Wildlife conservation","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":[0.0006794037,0.0002704583,0.0001403002,0.0006504073,0.000544807,0.0004704245,0.0004551796,0.0002424602,0.002089823],"category_scores_gemma":[0.001820358,0.0003126671,0.0001854905,0.0005527407,0.0002256942,0.0009152195,0.0006062589,0.000292475,0.0003678609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007873368,"about_ca_system_score_gemma":0.0007895624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07417762,"about_ca_topic_score_gemma":0.1735783,"domain_scores_codex":[0.9998228,0.00006255202,0.00001635919,0.00003855204,0.00002454287,0.00003527542],"domain_scores_gemma":[0.9992023,0.0003234452,0.0002805765,0.00002944279,0.00008294174,0.0000813372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002733939,0.0000390288,0.9896853,0.00003303196,0.00001460916,0.00005862991,0.0004764181,0.002012868,0.0002687935,0.00009281241,0.0003173737,0.006973871],"study_design_scores_gemma":[0.000008521035,0.0001683421,0.95187,0.00008807127,0.00003023437,0.0002404131,0.003915215,0.04165009,0.0002879954,0.0002148913,0.001504059,0.00002213458],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9969613,0.000083548,0.001233406,0.0000896889,0.000001545482,0.00003411786,0.0007971859,0.00001246649,0.000786615],"genre_scores_gemma":[0.9939236,0.000152198,0.004514864,0.00001957009,0.000002834139,0.00004265897,0.00102988,0.000004710962,0.0003096288],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.07417762,"threshold_uncertainty_score":0.1474917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02334139314604291,"score_gpt":0.2850918390112308,"score_spread":0.2617504458651879,"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."}}