{"id":"W1895284321","doi":"10.1017/s0376892915000181","title":"Economic-ecological evaluation of temporary biodiversity offsets in Alberta's boreal forest","year":2015,"lang":"en","type":"article","venue":"Environmental Conservation","topic":"Environmental Conservation and Management","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Biodiversity Monitoring Institute; University of Alberta; Alberta Innovates","funders":"","keywords":"Additionality; Biodiversity; Offset (computer science); Incentive; Natural resource economics; Taiga; Ecosystem services; Environmental resource management; Carbon offset; Habitat; Business; Economics; Ecology; Geography; Ecosystem; Climate change; Public economics; Forestry","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001010328,0.0001642657,0.000171747,0.00006727239,0.0000532216,0.00001157248,0.0001871775,0.0000955759,0.00170279],"category_scores_gemma":[0.00004454545,0.0001749927,0.00005228992,0.00009857708,0.0002595361,0.0004828187,0.000286877,0.00009040994,0.0008996605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001290253,"about_ca_system_score_gemma":0.000026184,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009592152,"about_ca_topic_score_gemma":0.009254847,"domain_scores_codex":[0.998271,0.0002108649,0.0003959406,0.0003614916,0.0005676944,0.0001930042],"domain_scores_gemma":[0.9993704,0.00005573685,0.0002062969,0.0002481508,0.000002824911,0.0001166212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005493375,0.0003325136,0.9859213,0.000002540757,0.000008070093,0.000002439754,0.0001796542,0.001681469,0.0002570623,0.00008060595,0.0102645,0.001214963],"study_design_scores_gemma":[0.001554072,0.0001283553,0.9751531,0.000004633625,0.00002232836,0.000002469113,0.0003804395,0.009710453,0.0003348994,0.0006399535,0.011893,0.000176278],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9828311,0.00001418703,0.00002542011,0.002410521,0.0001036301,0.0005991159,0.00001720043,0.00001417507,0.01398462],"genre_scores_gemma":[0.9978188,0.00001592554,0.0002721097,0.001301274,0.00001018775,0.00004350689,0.0003004083,0.000007660081,0.0002300948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0149877,"threshold_uncertainty_score":0.9998782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04088019739004211,"score_gpt":0.2368843152598749,"score_spread":0.1960041178698327,"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."}}