{"id":"W2991204790","doi":"10.5539/jsd.v12n6p62","title":"Application of the Theory of Planned Behavior in Predicting US Residents’ Willingness to Pay to Restore Degraded Tropical Rainforest Watersheds","year":2019,"lang":"en","type":"article","venue":"Journal of Sustainable Development","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Missouri; U.S. Department of Agriculture","keywords":"Willingness to pay; Rainforest; Theory of planned behavior; Tropical rainforest; Logistic regression; Socioeconomics; Sample (material); Psychology; Economics; Geography; Control (management); Ecology; Mathematics; Statistics; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001034552,0.00008812757,0.0002953214,0.0002387019,0.0000396817,0.00001242387,0.0002578172,0.0000592583,0.00003414178],"category_scores_gemma":[0.00008457286,0.00006829171,0.00005930275,0.0001875218,0.00002121502,0.0001574816,0.00008249361,0.0001139906,0.00001667761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005770466,"about_ca_system_score_gemma":0.00007380834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006819661,"about_ca_topic_score_gemma":0.0000144968,"domain_scores_codex":[0.9985587,0.00002364292,0.001005206,0.000135641,0.00008317794,0.0001936352],"domain_scores_gemma":[0.9990681,0.00004030896,0.0006174218,0.0001648615,0.00004841511,0.00006086221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001401348,0.0000666445,0.9906042,0.00004978158,0.00001702435,0.000002213301,0.002679578,0.002288189,0.0001183188,0.003687315,0.00002289804,0.0003236517],"study_design_scores_gemma":[0.0005341169,0.0001334258,0.9928784,0.00004694212,0.000005386451,0.000003043802,0.002940947,0.00007540914,0.001626967,0.0009097948,0.0007617398,0.00008376625],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974955,0.00004114015,0.001393878,0.000238625,0.0001305481,0.0005331718,0.000003200384,0.000001742623,0.000162154],"genre_scores_gemma":[0.9980268,0.000009082336,0.0009469708,0.00006669731,0.00002092818,0.0000294997,0.000002197468,0.00001064075,0.0008871732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00277752,"threshold_uncertainty_score":0.2784855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02702137349347371,"score_gpt":0.2079388479437966,"score_spread":0.1809174744503229,"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."}}