{"id":"W2776065208","doi":"10.1142/s2382624x18500066","title":"Temporal Reliability of Willingness to Pay for Payments for Environmental Services: Lessons from Lombok, Indonesia","year":2017,"lang":"en","type":"article","venue":"Water Economics and Policy","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Universitas Mataram","keywords":"Willingness to pay; Contingent valuation; Payment; Reliability (semiconductor); Econometrics; Actuarial science; Population; Environmental economics; Yield (engineering); Economics; Business; Environmental resource management; Statistics; Mathematics; Microeconomics; Finance; Environmental health","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003485733,0.0001719331,0.0004204265,0.00006920505,0.0002605485,0.0001049587,0.0002821393,0.0001090306,0.00004338982],"category_scores_gemma":[0.000008425398,0.0001575405,0.0001178689,0.000006412964,0.00007416095,0.0003144103,0.0001567363,0.00004017572,0.0000636021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001407263,"about_ca_system_score_gemma":0.000009943466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001638069,"about_ca_topic_score_gemma":0.0001043218,"domain_scores_codex":[0.9986547,0.000005285567,0.0005787482,0.0004770625,0.00001067413,0.0002734854],"domain_scores_gemma":[0.9989793,0.00003151681,0.0003676776,0.0005029661,0.000004294029,0.0001142734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009523067,0.0000917598,0.9848315,0.00006257403,0.00006324709,6.32805e-8,0.000961956,0.0002842735,0.0002089744,0.01019806,0.00003348522,0.003168866],"study_design_scores_gemma":[0.002272664,0.0001987552,0.8498304,0.00001545891,0.00002241076,6.016804e-7,0.0001149884,0.007464032,0.002729164,0.08501305,0.05189433,0.0004440935],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911721,0.00004002514,0.001025258,0.00293093,0.0002306995,0.0006229053,0.003689575,0.000005443181,0.0002830186],"genre_scores_gemma":[0.9969515,0.0002615477,0.001174225,0.0003868583,0.0002409251,0.0001409432,0.000368748,0.00003226288,0.0004429801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1350011,"threshold_uncertainty_score":0.6424317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0640223602537068,"score_gpt":0.2586918176311497,"score_spread":0.1946694573774429,"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."}}