{"id":"W2802117134","doi":"10.1111/jbi.13240","title":"Modelling broad‐scale wolverine occupancy in a remote boreal region using multi‐year aerial survey data","year":2018,"lang":"en","type":"article","venue":"Journal of Biogeography","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Natural Resources and Forestry; Cochrane; University of Calgary; Wildlife Conservation Society Canada","funders":"W. Garfield Weston Foundation; Environment Canada; Ministry of Natural Resources; World Wildlife Fund","keywords":"Occupancy; Physical geography; Geography; Carnivore; Environmental science; Taiga; Ecology; Cartography; Forestry; Biology","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":[0.001841036,0.0004171567,0.0003804969,0.0005961654,0.0003311523,0.0007906337,0.001164412,0.000560254,0.001160477],"category_scores_gemma":[0.002560396,0.0005779237,0.0007866743,0.000470348,0.0004161524,0.0006309683,0.0006152118,0.0003374479,0.0001117907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00111979,"about_ca_system_score_gemma":0.0006606587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1543955,"about_ca_topic_score_gemma":0.2308789,"domain_scores_codex":[0.9994097,0.0002478559,0.00003094815,0.0001933456,0.00003742617,0.00008078466],"domain_scores_gemma":[0.9979984,0.001071627,0.0005055089,0.0001411091,0.0001025918,0.0001807114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001760394,0.0001503478,0.6948084,0.00003927655,0.0002733516,0.0002123165,0.0002411567,0.2956883,0.0006607968,0.0004743656,0.0003351936,0.006940342],"study_design_scores_gemma":[0.00002307394,0.000153962,0.2417055,0.00001742919,0.00004287263,0.00006271974,0.0002986883,0.7568579,0.0001216578,0.0003590411,0.0003372744,0.00001987513],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996205,0.00005672038,0.003071432,0.00004386385,0.000003065903,0.00001542806,0.0003841558,0.00002814677,0.00019214],"genre_scores_gemma":[0.9969405,0.00002809614,0.002395166,0.000009577525,0.00000372837,0.00001931363,0.0004152332,0.000004631198,0.0001837999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1543955,"threshold_uncertainty_score":0.3069937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0688059934315333,"score_gpt":0.2840216650751964,"score_spread":0.2152156716436631,"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."}}