{"id":"W2590437765","doi":"10.1371/journal.pone.0170759","title":"The impacts of forest management strategies for woodland caribou vary across biogeographic gradients","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University; Ministry of Natural Resources and Forestry; Laurentian University","funders":"Ontario Ministry of Natural Resources and Forestry; Ministry of Natural Resources","keywords":"Woodland caribou; Habitat; Wildlife; Disturbance (geology); Ecology; Wildlife management; Forest management; Geography; Wildlife conservation; Woodland; Population; Forest ecology; Range (aeronautics); Taiga; Spatial ecology; Ecosystem; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007374996,0.0001479708,0.0001835982,0.0006546305,0.000468028,0.0006488385,0.0002324352,0.0001973761,0.0005772507],"category_scores_gemma":[0.00208965,0.00009447045,0.0001701047,0.0004944274,0.000555535,0.0003340358,0.0004878269,0.0001773852,0.0000837382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004401674,"about_ca_system_score_gemma":0.0005163741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02411663,"about_ca_topic_score_gemma":0.1384765,"domain_scores_codex":[0.9994354,0.0002782209,0.00002952032,0.00008359151,0.00008194828,0.0000912753],"domain_scores_gemma":[0.9988282,0.000380072,0.0003718855,0.00009000471,0.000172821,0.0001570999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005021278,0.00009302663,0.9783375,0.00004255241,0.0001197125,0.0001094311,0.001100352,0.0004885293,0.004419187,0.0001388593,0.00009814547,0.01500243],"study_design_scores_gemma":[7.121146e-7,0.00004975465,0.9984701,0.000008904419,0.00001086437,0.0000439971,0.0008541628,0.0001456204,0.00009486006,0.00004846231,0.0002699785,0.000002617227],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986625,0.0002774115,0.0001750188,0.00004145809,0.000002595657,0.000005867465,0.00002586392,0.000003172662,0.0008062174],"genre_scores_gemma":[0.9993754,0.0001790614,0.0002588898,0.00002402679,0.000001999806,0.000004907513,0.00003387257,0.000001496646,0.0001203937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02411663,"threshold_uncertainty_score":0.04795253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02866897376235574,"score_gpt":0.2457743761953388,"score_spread":0.2171054024329831,"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."}}