{"id":"W1967418138","doi":"10.1007/s10980-011-9647-6","title":"Assessing the influence of resource covariates at multiple spatial scales: an application to forest-dwelling caribou faced with intensive human activity","year":2011,"lang":"en","type":"article","venue":"Landscape Ecology","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":104,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministère des Ressources naturelles et des Forêts; Université Laval; Natural Sciences and Engineering Research Council of Canada; Ministère des Ressources naturelles et des Forêts (Québec); Université du Québec à Rimouski","funders":"","keywords":"Landscape ecology; Geography; Ecology; Nature Conservation; Covariate; Resource (disambiguation); Environmental resource management; Environmental science; Biology; Habitat; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0002690551,0.0001045537,0.0001518213,0.00002697318,0.0003132439,0.00001069606,0.00022387,0.0001132531,0.00009864849],"category_scores_gemma":[0.00009391723,0.00007541414,0.00001894966,0.0001276499,0.0002145643,0.0002057634,0.0001477422,0.0001177308,0.00003966887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006168259,"about_ca_system_score_gemma":0.00001174146,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002392995,"about_ca_topic_score_gemma":0.07652258,"domain_scores_codex":[0.9991142,0.0001407261,0.0001695652,0.0002814406,0.0000909371,0.000203104],"domain_scores_gemma":[0.9992477,0.0001998577,0.0001892863,0.0002699009,0.00003911194,0.00005419202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001054981,0.00005364906,0.9701434,0.000002844577,0.00001053706,0.000001488406,0.001475265,0.02009933,0.007672842,0.0000330481,0.00004508504,0.0003570254],"study_design_scores_gemma":[0.0002837722,0.000271879,0.9889342,0.000003808331,0.00001819162,0.000006344618,0.0003847173,0.00807956,0.001712462,0.0001429656,0.00006465537,0.000097513],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949713,9.778672e-7,0.004081919,0.0002072398,0.00002645643,0.0003673866,0.000003369365,0.00002583651,0.0003155296],"genre_scores_gemma":[0.998855,3.540242e-7,0.0004078895,0.0005848526,0.00002042119,0.00008183413,0.00001770778,0.000009218333,0.00002272619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07412959,"threshold_uncertainty_score":0.9403285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01547407598097774,"score_gpt":0.2450514712737897,"score_spread":0.2295773952928119,"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."}}