{"id":"W2795401294","doi":"10.1080/09640568.2017.1406340","title":"Barriers to achieving additionality in carbon offsets: a regulatory risk perspective","year":2018,"lang":"en","type":"article","venue":"Journal of Environmental Planning and Management","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Polymer Source (Canada)","funders":"","keywords":"Additionality; Carbon offset; Greenhouse gas; Mandate; Clean Development Mechanism; Emissions trading; Business; Offset (computer science); Environmental economics; Environmental science; Natural resource economics; Environmental resource management; Environmental planning; Economics; Computer science; Political science; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01617319,0.0006120527,0.0006522646,0.001606835,0.003990631,0.01121579,0.002681134,0.004801201,0.007562525],"category_scores_gemma":[0.04009756,0.0005013004,0.0008627273,0.001269277,0.009289997,0.006783825,0.004972424,0.006021937,0.0004057995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01320121,"about_ca_system_score_gemma":0.02183601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08885211,"about_ca_topic_score_gemma":0.075793,"domain_scores_codex":[0.981994,0.005682271,0.0005867568,0.001188924,0.006469454,0.004078596],"domain_scores_gemma":[0.9577252,0.0264723,0.004489375,0.001683901,0.007492921,0.002136282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004560119,0.00009447479,0.006710616,0.0001040879,0.00003898118,0.0004544513,0.002956485,0.02356006,0.0007357511,0.9530736,0.002642035,0.009583799],"study_design_scores_gemma":[0.00006304712,0.0001723871,0.01374386,0.0007647339,0.000133778,0.0004972407,0.01396957,0.02424454,0.002540146,0.8437154,0.09995726,0.000197956],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3071752,0.003886485,0.1274576,0.08682907,0.0002121674,0.0004043893,0.0003870382,0.000190868,0.4734571],"genre_scores_gemma":[0.9876688,0.0005462173,0.004746032,0.001145005,0.00006813363,0.00006749912,0.00004508725,0.00002659575,0.005686579],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08885211,"threshold_uncertainty_score":0.1766698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02551161263139386,"score_gpt":0.2358996229071538,"score_spread":0.21038801027576,"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."}}