{"id":"W2126237824","doi":"10.1111/j.1365-2664.2010.01830.x","title":"Bioclimate envelope model predictions for natural resource management: dealing with uncertainty","year":2010,"lang":"en","type":"article","venue":"Journal of Applied Ecology","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta-Pacific Forest Industries","keywords":"Edaphic; Climate change; Reforestation; Range (aeronautics); Species distribution; Environmental science; Habitat; Ecology; Econometrics; Environmental resource management; Mathematics; Agroforestry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002507183,0.00009357432,0.0001417581,0.0000459838,0.0001789898,0.00001868667,0.0001937111,0.00006847956,0.003059495],"category_scores_gemma":[0.000007449697,0.00007168189,0.00005109891,0.00009209051,0.0001415913,0.00006146429,0.00007116645,0.0002234711,0.0000491231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001618556,"about_ca_system_score_gemma":0.000008470816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001972267,"about_ca_topic_score_gemma":0.0002520509,"domain_scores_codex":[0.9992481,0.000004467391,0.0002333357,0.0001319473,0.0001417994,0.0002403061],"domain_scores_gemma":[0.999541,0.00003711479,0.0002116403,0.0001053716,0.0000193323,0.00008552537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00516338,0.00107648,0.01474889,0.000148684,0.0006682398,0.00008722528,0.001935392,0.4468484,0.07935563,0.3558978,0.08036483,0.01370499],"study_design_scores_gemma":[0.01360641,0.001320258,0.1721372,0.00003584288,0.0006977064,0.0007038026,0.0122948,0.1066129,0.005082446,0.0172657,0.6688455,0.001397568],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8937187,0.000005388357,0.002931313,0.0009383392,0.0002699463,0.000306406,0.00003717139,0.00002530653,0.1017675],"genre_scores_gemma":[0.9940315,0.00002227577,0.005211455,0.0004350169,0.00004899396,0.00002234519,0.00001609031,0.00001043397,0.0002018623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5884807,"threshold_uncertainty_score":0.9978518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01153792095942024,"score_gpt":0.2294860506303401,"score_spread":0.2179481296709199,"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."}}