{"id":"W4213211630","doi":"10.1093/ornithapp/duab063","title":"Sequential use of niche and occupancy models identifies conservation and research priority areas for two data-poor endemic birds from the Colombian Andes","year":2021,"lang":"en","type":"article","venue":"Ornithological applications","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Occupancy; Geography; Environmental niche modelling; Species distribution; Ecology; Range (aeronautics); Niche; Distribution (mathematics); Endemism; Ecological niche; Data deficient; Population; Conservation status; Habitat; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004560302,0.00007224688,0.0001142196,0.000009874381,0.0003507796,0.0001035485,0.0002094516,0.00007059616,0.001243059],"category_scores_gemma":[0.0002762865,0.00005276931,0.00001932596,0.0002263578,0.0007494716,0.000209954,0.0005629159,0.0001233682,0.00001751604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004943083,"about_ca_system_score_gemma":0.00001830195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002070268,"about_ca_topic_score_gemma":0.001601419,"domain_scores_codex":[0.998965,0.0001361848,0.000176505,0.0003782509,0.0001883635,0.0001557366],"domain_scores_gemma":[0.9986811,0.0007305379,0.00006117338,0.0003942912,0.00007450318,0.00005834678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001203206,0.00055885,0.7765405,0.00003556143,0.00004759214,0.000004011879,0.0005287462,0.00001743226,0.1650238,0.02045951,0.0280393,0.00862436],"study_design_scores_gemma":[0.0006206743,0.00004668345,0.9142343,0.000009750505,0.00006305648,0.00001440095,0.001639126,0.001313649,0.004655558,0.02547866,0.05175923,0.0001649331],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867441,0.0002027216,0.007364184,0.002197464,0.00001550119,0.0005567444,0.002450279,0.00002525019,0.0004437743],"genre_scores_gemma":[0.9967648,0.0003398201,0.001229533,0.0002678357,0.00002233417,0.0002593686,0.0009929977,0.000004765936,0.0001185159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1603682,"threshold_uncertainty_score":0.99967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3329867559798356,"score_gpt":0.4020573820413588,"score_spread":0.0690706260615232,"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."}}