{"id":"W2038038785","doi":"10.1080/19390450802614466","title":"Estimating the Willingness to Pay for the Benefit of AES Using the Contingent Valuation Method","year":2009,"lang":"en","type":"article","venue":"Journal of Natural Resources Policy Research","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Willingness to pay; Contingent valuation; Tobit model; Valuation (finance); Economics; Willingness to accept; Econometrics; Actuarial science; Public economics; Microeconomics; Business; Finance","routes":{"ca_aff":true,"ca_fund":false,"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":[0.006815993,0.0003977026,0.0006024302,0.001366747,0.0003451637,0.001318983,0.0007262888,0.0008104942,0.005524316],"category_scores_gemma":[0.03009426,0.0002960344,0.0007007045,0.001308843,0.0005059665,0.001132796,0.0006789924,0.0007983103,0.0004226185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008257523,"about_ca_system_score_gemma":0.0004909034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005542616,"about_ca_topic_score_gemma":0.00252653,"domain_scores_codex":[0.9956197,0.003637321,0.0001118845,0.0001749528,0.000295095,0.0001610011],"domain_scores_gemma":[0.9621829,0.03383499,0.001720413,0.001254654,0.0007032239,0.0003037633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002853754,0.001284296,0.5984221,0.0002652377,0.0008437232,0.000881668,0.001915055,0.2477019,0.003967958,0.02887313,0.00168113,0.1113101],"study_design_scores_gemma":[0.000157063,0.0009735492,0.2915857,0.000084402,0.0001927976,0.000413441,0.002253228,0.6791381,0.002855173,0.01999305,0.002230275,0.000123194],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9747245,0.00008613158,0.02235778,0.0001327466,0.000008762685,0.0001437826,0.0004614041,0.00001547661,0.002069458],"genre_scores_gemma":[0.9930251,0.00003322789,0.006286417,0.000007565714,0.000003827366,0.00007511974,0.0002320534,0.000002285932,0.0003345293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006815993,"threshold_uncertainty_score":0.03604686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3263576036442484,"score_gpt":0.4297855424957512,"score_spread":0.1034279388515028,"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."}}