{"id":"W4414447397","doi":"10.1016/j.gloenvcha.2025.103068","title":"Mitigation deterrence and unrealistic expectations: the future costs of forest carbon offsets","year":2025,"lang":"en","type":"article","venue":"Global Environmental Change","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"HORIZON EUROPE Reforming and enhancing the European Research and Innovation system; University of British Columbia Graduate School; International Institute for Applied Systems Analysis; University of British Columbia","keywords":"Greenhouse gas; Reducing emissions from deforestation and forest degradation; Climate change mitigation; Climate change; Carbon offset; Global warming; Renewable energy; Carbon tax; Deforestation (computer science)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001389578,0.0003978882,0.000394875,0.0003309961,0.000526529,0.002049525,0.0006730398,0.001144983,0.005270958],"category_scores_gemma":[0.006228933,0.0002606281,0.0005970917,0.0004181676,0.001035108,0.002408701,0.00099293,0.001673614,0.0002089596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002059612,"about_ca_system_score_gemma":0.001899767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01055351,"about_ca_topic_score_gemma":0.01247452,"domain_scores_codex":[0.9992725,0.0003082828,0.00001994188,0.00006878353,0.0001688247,0.0001617092],"domain_scores_gemma":[0.9965396,0.002102367,0.0008220129,0.0001763778,0.0002288619,0.0001308735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005410343,0.0002483609,0.04189237,0.0002296082,0.0001905566,0.00092021,0.0003394629,0.7144586,0.002721097,0.1836683,0.00246526,0.05232509],"study_design_scores_gemma":[0.00009636812,0.0005840345,0.0731174,0.0002161637,0.0001974438,0.0005583705,0.00203708,0.6579318,0.004093232,0.2511053,0.009883235,0.0001795519],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9358073,0.0007135671,0.01456864,0.003349947,0.00004693012,0.00005648892,0.0004341799,0.00004495853,0.0449779],"genre_scores_gemma":[0.9978232,0.0001691395,0.0006519941,0.00007180815,0.000005257804,0.000009620312,0.00004202135,0.000003948322,0.001222865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01055351,"threshold_uncertainty_score":0.02098417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03027400537347969,"score_gpt":0.2348220737530934,"score_spread":0.2045480683796137,"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."}}