{"id":"W1982654582","doi":"10.1525/auk.2012.11190","title":"Using binomial distance-sampling models to estimate the effective detection radius of point-count surveys across boreal Canada","year":2012,"lang":"en","type":"article","venue":"The Auk","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; University of Alberta","funders":"U.S. Fish and Wildlife Service; University of Alberta","keywords":"Statistics; Negative binomial distribution; Count data; Goodness of fit; Sampling (signal processing); Distance sampling; Population; Mathematics; Multinomial distribution; Poisson distribution; Transect; Ecology; Demography; Biology; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009949771,0.00008859458,0.0001007284,0.000004942177,0.0003707956,0.000009356019,0.0001888915,0.00003697575,0.00003724133],"category_scores_gemma":[0.00002464968,0.00005289037,0.00002662961,0.0001137605,0.0001722183,0.0001471771,0.0001207087,0.0001100197,0.00001278289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000421887,"about_ca_system_score_gemma":0.00001963172,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2873984,"about_ca_topic_score_gemma":0.6281727,"domain_scores_codex":[0.9991364,0.0001725271,0.0001169356,0.0001146523,0.0001371335,0.0003223925],"domain_scores_gemma":[0.9995148,0.0001529701,0.00006927613,0.0002005808,0.000006310129,0.0000561005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001362945,0.00008180429,0.7966442,0.000006773069,0.0000257906,0.000002656916,0.005200021,0.1396725,0.02276435,0.00003246502,0.00009738501,0.03533582],"study_design_scores_gemma":[0.0001134674,0.00002501785,0.9861352,0.000004092624,0.0000225347,0.000008414039,0.0001671896,0.003428414,0.009846502,0.0001139952,0.00005411107,0.0000810388],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9610325,0.00001299525,0.03811555,0.00005499595,0.0003067559,0.0002975227,0.00002640544,0.000008411579,0.0001448356],"genre_scores_gemma":[0.9996243,4.517408e-7,0.0002016062,0.00006384094,0.00004734385,0.00001990556,0.000001376364,0.000008409491,0.00003278878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3407743,"threshold_uncertainty_score":0.7173468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0330622969521983,"score_gpt":0.3076274944363496,"score_spread":0.2745651974841513,"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."}}