{"id":"W1950356037","doi":"10.22621/cfn.v128i2.1565","title":"Estimating breeding bird survey trends and annual indices for Canada: how do the new hierarchical Bayesian estimates differ from previous estimates?","year":2014,"lang":"en","type":"article","venue":"The Canadian Field-Naturalist","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Breeding bird survey; Bayesian hierarchical modeling; Bayesian probability; Geography; Statistical model; Hierarchical database model; Population; Statistics; Deviance information criterion; Multilevel model; Bayesian inference; Econometrics; Computer science; Demography; Mathematics; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.01264338,0.0005447039,0.0005076791,0.003531811,0.001170831,0.00383878,0.002004636,0.000727783,0.001664142],"category_scores_gemma":[0.06328073,0.0004971585,0.0008365214,0.005433938,0.001451672,0.003810374,0.001111495,0.002098219,0.0002730924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02201863,"about_ca_system_score_gemma":0.01745545,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9381988,"about_ca_topic_score_gemma":0.9571917,"domain_scores_codex":[0.9956666,0.001179502,0.0002405808,0.0005612558,0.002057921,0.0002941048],"domain_scores_gemma":[0.982262,0.00798477,0.00129362,0.00112763,0.006958149,0.0003737742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001148616,0.00006773675,0.2570231,0.0005619365,0.0008196429,0.0001627439,0.002925812,0.1031213,0.0003822874,0.211359,0.03353446,0.389927],"study_design_scores_gemma":[0.00007367018,0.00007464436,0.2621701,0.001369498,0.0006287025,0.0002328885,0.002649138,0.4092578,0.0009483489,0.2316471,0.09061238,0.0003356371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2061129,0.02263955,0.6545797,0.05083492,0.0007936053,0.0002426808,0.01227572,0.0006645976,0.05185639],"genre_scores_gemma":[0.7317867,0.01207897,0.2375569,0.002411979,0.0004843842,0.0001378594,0.007617276,0.0003145978,0.007611296],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0618012,"threshold_uncertainty_score":0.1597571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03731133023295416,"score_gpt":0.2171796634413653,"score_spread":0.1798683332084112,"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."}}