{"id":"W3180034992","doi":"10.3389/fevo.2021.663043","title":"Benefits Beyond Borders: Assessing Landowner Willingness-to-Accept Incentives for Conservation Outside Protected Areas","year":2021,"lang":"en","type":"article","venue":"Frontiers in Ecology and Evolution","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Oracle","keywords":"Wildlife; Incentive; Livelihood; Habitat; Land tenure; Business; Payment; Wildlife conservation; Natural resource economics; Land use; Geography; Willingness to pay; Environmental resource management; Environmental planning; Agroforestry; Agriculture; Ecology; Economics; Environmental science; Finance","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003713783,0.0001033061,0.00026868,0.0001347337,0.0001519997,0.00003876974,0.00004959972,0.0001569448,0.00003198929],"category_scores_gemma":[0.0001851168,0.0001314841,0.00003638593,0.0001312879,0.00005708049,0.0003835405,0.00003464027,0.00008412241,0.00001672398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002853567,"about_ca_system_score_gemma":0.00003129238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005584858,"about_ca_topic_score_gemma":0.0002075275,"domain_scores_codex":[0.9990146,0.0000300571,0.0003579119,0.0003645625,0.00001588364,0.0002169597],"domain_scores_gemma":[0.9996293,0.00003854041,0.0001644963,0.0001012871,0.00002404413,0.00004234113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003198711,0.00005102438,0.9906048,0.00001823242,0.00002385207,4.213654e-7,0.0002032851,0.001114039,0.00003699659,0.005621827,0.0008207656,0.001472754],"study_design_scores_gemma":[0.00099193,0.0000440895,0.9568062,0.00001481019,0.000007790997,0.00000200297,0.0005016054,0.01066424,0.00006486244,0.02941999,0.001329403,0.0001530276],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9254532,0.001410539,0.06995929,0.001305503,0.000829665,0.0004241976,0.00004734384,0.00001611598,0.000554164],"genre_scores_gemma":[0.9834231,0.0001580605,0.01542246,0.000401888,0.00005442667,0.0001595591,0.0001392466,0.00001223516,0.0002290181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05796992,"threshold_uncertainty_score":0.5361767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03710120459539504,"score_gpt":0.2300244686176311,"score_spread":0.1929232640222361,"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."}}