{"id":"W3042159750","doi":"10.1002/ecs2.3181","title":"Population‐level monitoring of stress in grizzly bears between 2004 and 2014","year":2020,"lang":"en","type":"article","venue":"Ecosphere","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Forests; Foothills Medical Centre; University of British Columbia; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Forest Resource Improvement Association of Alberta; Seven Generations Energy; fRI Research; Shell Canada; Shell","keywords":"Ecology; Ursus; Population; Disturbance (geology); Grizzly Bears; Habitat; Geography; Environmental science; Biology; Demography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003348403,0.0001760117,0.0001292141,0.0004663824,0.0004495509,0.0003564828,0.0003921734,0.0001872731,0.0004919881],"category_scores_gemma":[0.0004280014,0.0001242311,0.0001587081,0.0004592755,0.000315615,0.0001515474,0.0002880553,0.0002487677,0.00009005769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001455599,"about_ca_system_score_gemma":0.0006510961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3460405,"about_ca_topic_score_gemma":0.6586551,"domain_scores_codex":[0.9998672,0.00001763739,0.000004579512,0.00003571502,0.00004223468,0.00003265568],"domain_scores_gemma":[0.9996127,0.00002254634,0.0001382994,0.0000223162,0.0001169498,0.00008716065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003142142,0.00001275887,0.9981186,0.000003178745,0.00001594478,0.0000144094,0.0001702895,0.0000874451,0.0004688062,0.00001010944,0.0001052108,0.0009618663],"study_design_scores_gemma":[3.952651e-7,0.000009940307,0.9996917,9.076991e-7,0.000002362854,0.000006876761,0.0001447159,0.00005467127,0.00002596896,0.000002695969,0.0000591544,6.619124e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992657,0.00004385184,0.00006364451,0.00001488865,0.000003146235,0.000004788887,0.0003524248,0.000003490887,0.0002480297],"genre_scores_gemma":[0.9989375,0.00003592997,0.0001401894,0.00001103415,0.000003855559,0.000007360587,0.0005917072,6.897812e-7,0.0002717655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3460405,"threshold_uncertainty_score":0.6880528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02318866328089303,"score_gpt":0.2306147063566437,"score_spread":0.2074260430757507,"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."}}