{"id":"W3124401437","doi":"","title":"A Box-Cox double-hurdle model of wildlife valuation: the citizen’s perspective","year":2004,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Perspective (graphical); Contingent valuation; Wildlife; Valuation (finance); Payment; Actuarial science; Wildlife conservation; Willingness to pay; Economics; Public economics; Econometrics; Geography; Microeconomics; Computer science; Ecology; Accounting; Finance","routes":{"ca_aff":true,"ca_fund":false,"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":[0.01300427,0.002385703,0.004279007,0.002230789,0.001107923,0.007020383,0.0054173,0.005995397,0.02031988],"category_scores_gemma":[0.02340792,0.002034812,0.003881114,0.003414956,0.003606928,0.006060241,0.00237222,0.005599576,0.003949462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00301196,"about_ca_system_score_gemma":0.002125005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01525267,"about_ca_topic_score_gemma":0.00969978,"domain_scores_codex":[0.9939475,0.003635459,0.000189505,0.0007975425,0.0005467192,0.000883309],"domain_scores_gemma":[0.9799364,0.01521284,0.001500719,0.001053033,0.001480777,0.0008162238],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005978419,0.0002989489,0.005578649,0.0002772809,0.0002408522,0.0008378574,0.0007452804,0.2907076,0.0004859869,0.6814758,0.005886426,0.01286739],"study_design_scores_gemma":[0.0002426502,0.0002027163,0.001234715,0.00007214251,0.0001003057,0.0002214965,0.000318046,0.7676611,0.0001505799,0.2258055,0.003885954,0.0001047159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1187892,0.002135116,0.8308659,0.006626877,0.0005322121,0.0006619298,0.002621013,0.0003838972,0.0373839],"genre_scores_gemma":[0.824966,0.003515986,0.08140539,0.0007971897,0.0006085592,0.001166293,0.001794902,0.0001538783,0.08559188],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02031988,"threshold_uncertainty_score":0.06877398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1655274116846791,"score_gpt":0.3094425877701629,"score_spread":0.1439151760854838,"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."}}