{"id":"W1904055772","doi":"10.1002/wsb.475","title":"Using ungulate biomass to estimate abundance of wolves in British Columbia","year":2014,"lang":"en","type":"article","venue":"Wildlife Society Bulletin","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Forests","funders":"","keywords":"Ungulate; Canis; Abundance (ecology); Biomass (ecology); Geography; Wildlife; Ecology; Scale (ratio); Physical geography; Biology; Habitat; Cartography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005713071,0.00009395961,0.0002137831,0.00000959556,0.0001565712,0.00005395622,0.0002147576,0.0001327974,0.001333653],"category_scores_gemma":[0.0001127485,0.0001563448,0.00009399022,0.0003135764,0.0002464471,0.00006623549,0.0001567292,0.0001134443,0.0001716384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001176551,"about_ca_system_score_gemma":0.00001564992,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02703424,"about_ca_topic_score_gemma":0.0266094,"domain_scores_codex":[0.9987543,0.00008196949,0.0003162603,0.0003376345,0.0001927516,0.0003171311],"domain_scores_gemma":[0.9995036,0.00007767351,0.0001200128,0.0002001032,0.00001277594,0.00008586132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003921287,0.00005595463,0.9412348,0.00001448045,0.000007527691,0.000001649904,0.0002449841,0.002033303,0.001135937,0.000006218491,0.05447588,0.0007853556],"study_design_scores_gemma":[0.0003663386,0.00004011212,0.9699903,0.00006804329,0.00000833666,0.000006381169,0.00006273176,0.003986467,0.00003530127,0.0002205465,0.02503733,0.00017814],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958076,0.00001490792,0.001161216,0.002163292,0.0001094095,0.0002037145,0.000005461053,0.00003707783,0.0004973262],"genre_scores_gemma":[0.9713476,0.000005550286,0.02348567,0.004310686,0.000035033,0.00001648426,0.000004572564,0.00001755852,0.0007768183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02943855,"threshold_uncertainty_score":0.9995793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009890454590737103,"score_gpt":0.2394835656680034,"score_spread":0.2295931110772663,"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."}}