{"id":"W2164443402","doi":"10.1111/acv.12140","title":"Estimating occupancy using spatially and temporally replicated snow surveys","year":2014,"lang":"en","type":"article","venue":"Animal Conservation","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parks Canada","funders":"Parks Canada","keywords":"Occupancy; Spatial correlation; Statistics; Spatial ecology; Spatial analysis; Spatial distribution; Statistical power; Sampling (signal processing); Snow; Correlation; Environmental science; Ecology; Geography; Computer science; Mathematics; Biology; Meteorology","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":[0.007888098,0.000462011,0.0008548798,0.0009604732,0.0003574191,0.001046297,0.001666369,0.0007823473,0.00083553],"category_scores_gemma":[0.01914674,0.0009042357,0.001441425,0.0009216408,0.0006538295,0.001289666,0.001017791,0.0005973419,0.0002000552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001326579,"about_ca_system_score_gemma":0.0007725522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02341339,"about_ca_topic_score_gemma":0.02570719,"domain_scores_codex":[0.9940519,0.003856129,0.0002329984,0.001190913,0.0004377813,0.000230319],"domain_scores_gemma":[0.9812818,0.01119799,0.003927551,0.002283966,0.0009586723,0.0003500384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005972486,0.0002132139,0.5116378,0.0000955486,0.001156983,0.0001463826,0.0005367077,0.4540135,0.003648415,0.00114267,0.000290823,0.02652064],"study_design_scores_gemma":[0.0000282077,0.0001885994,0.07472086,0.00001580457,0.0001130014,0.00007715196,0.0001333356,0.9222423,0.0008142907,0.001416762,0.000213901,0.00003574566],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9215536,0.00006461277,0.07738421,0.00004387528,0.000008880585,0.00005609925,0.0002462623,0.0001683402,0.0004741656],"genre_scores_gemma":[0.9852833,0.00001573201,0.0143297,0.00001289072,0.000005200563,0.00003589857,0.0001928997,0.00001198933,0.0001125583],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02341339,"threshold_uncertainty_score":0.04655421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02744769095559101,"score_gpt":0.2557787114545951,"score_spread":0.2283310204990041,"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."}}