{"id":"W2100408661","doi":"10.2981/0909-6396(2007)13[52:ewggps]2.0.co;2","title":"Estimating wolverine<i>Gulo gulo</i>population size using quadrat sampling of tracks in snow","year":2007,"lang":"en","type":"article","venue":"Wildlife Biology","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parks Canada","funders":"U.S. Department of Agriculture; U.S. Fish and Wildlife Service; Parks Canada; National Park Service; U.S. Forest Service; Massachusetts Department of Fish and Game; Alaska Department of Fish and Game","keywords":"Quadrat; Sampling (signal processing); Snow; Environmental science; Stratified sampling; Statistics; Estimator; Population; Hydrology (agriculture); Physical geography; Geography; Population density; Ecology; Mathematics; Transect; Biology; Demography; Meteorology; Geology","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":[0.0006555127,0.000246342,0.0003183123,0.001056233,0.0002567253,0.0003500421,0.0003386835,0.0001822992,0.0005262699],"category_scores_gemma":[0.001429054,0.0002043373,0.0001671727,0.0005749155,0.0002742279,0.000315826,0.0002625934,0.0001370252,0.0001444457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003791425,"about_ca_system_score_gemma":0.0001389788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02672071,"about_ca_topic_score_gemma":0.08642246,"domain_scores_codex":[0.9996117,0.00009890478,0.00002814322,0.0001723682,0.00005569133,0.00003333108],"domain_scores_gemma":[0.9992222,0.000167387,0.0003545524,0.00006928838,0.0001323757,0.00005425318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005532542,0.0000216896,0.9802904,0.00002377462,0.0000636368,0.00006551536,0.0003669181,0.001313608,0.006348283,0.00005627873,0.0001418714,0.01125272],"study_design_scores_gemma":[0.000002190787,0.00005520639,0.9956874,0.000005987636,0.00001185458,0.0001082731,0.0001181508,0.003060492,0.000685277,0.00002980662,0.0002301109,0.000005220526],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956447,0.0000782874,0.003664844,0.000006057066,0.00000129692,0.00002239631,0.0002771353,0.00002542711,0.0002798387],"genre_scores_gemma":[0.9899549,0.00006193939,0.00916815,0.00001312232,0.000002237773,0.00005147841,0.0005438283,0.000006764474,0.0001974845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02672071,"threshold_uncertainty_score":0.05313033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02607607982615303,"score_gpt":0.2954065476614501,"score_spread":0.2693304678352971,"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."}}