{"id":"W2800482517","doi":"10.1002/ece3.4023","title":"Assessing the impacts of imperfect detection on estimates of diversity and community structure through multispecies occupancy modeling","year":2018,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Natural Resources and Forestry; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; Ontario Ministry of Natural Resources and Forestry","keywords":"Species richness; Occupancy; Sampling (signal processing); Community structure; Imperfect; Ecology; Sampling design; Sampling bias; Geography; Computer science; Statistics; Sample size determination; Biology; Mathematics; Population","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":[0.0491364,0.0008704018,0.001239037,0.001911163,0.001404484,0.002218873,0.002715954,0.001188889,0.0008217706],"category_scores_gemma":[0.1363762,0.001286674,0.001431579,0.00252653,0.002583352,0.003538301,0.003445683,0.001772955,0.0002522887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002423036,"about_ca_system_score_gemma":0.001406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02973273,"about_ca_topic_score_gemma":0.04283231,"domain_scores_codex":[0.9677058,0.02062656,0.002030016,0.004857306,0.003579098,0.00120125],"domain_scores_gemma":[0.8330933,0.1207698,0.02027467,0.01913671,0.005639982,0.00108556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002006813,0.00008809501,0.7713785,0.0001905985,0.0008113476,0.0001861943,0.001184686,0.1975195,0.001888527,0.003508475,0.0007243907,0.02231896],"study_design_scores_gemma":[0.00002103806,0.0002097272,0.3047999,0.00009525434,0.000206257,0.0003489483,0.0006720832,0.6767054,0.003356168,0.01147421,0.002006987,0.0001039812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7297093,0.0004026692,0.2661745,0.0004820602,0.00005045897,0.0001654295,0.001108125,0.000357137,0.001550403],"genre_scores_gemma":[0.9597086,0.00004807802,0.03909884,0.0001012585,0.00001308636,0.00008691918,0.000664958,0.00005027297,0.0002279652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0491364,"threshold_uncertainty_score":0.2598612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02782947350885224,"score_gpt":0.2721140588965522,"score_spread":0.2442845853876999,"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."}}