{"id":"W4292478934","doi":"10.1111/nrm.12354","title":"Polluting resource extraction and climate risk","year":2022,"lang":"en","type":"article","venue":"Natural Resource Modeling","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; Concordia University","funders":"","keywords":"Shadow price; Natural resource economics; Economics; Scarcity; Carbon sequestration; Carbon tax; Natural resource; Climate change; Extraction (chemistry); Greenhouse gas; Atmosphere (unit); Fossil fuel; Term (time); Shadow (psychology); Resource (disambiguation); Environmental science; Econometrics; Microeconomics; Ecology; Carbon dioxide; Biology; Meteorology; Mathematical optimization; Computer science; Chemistry; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001248352,0.0001738546,0.0003023795,0.0002762877,0.001086841,0.000106061,0.0001930133,0.00007569259,0.0001749217],"category_scores_gemma":[0.0001660452,0.0002243121,0.0001098421,0.0001775544,0.00002729655,0.0001764543,0.0003791409,0.0007360574,0.00005244004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002450144,"about_ca_system_score_gemma":0.000005565641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004745023,"about_ca_topic_score_gemma":0.00003211457,"domain_scores_codex":[0.998333,0.00003954147,0.0005597866,0.0005073089,0.00005186598,0.0005084405],"domain_scores_gemma":[0.9991783,0.00009796804,0.0003759591,0.000246851,0.000009147797,0.00009177503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008755362,0.0002344356,0.05827038,0.0002188957,0.0002402314,0.00003406382,0.01658055,0.7081003,0.00052301,0.1610188,0.002326482,0.0515773],"study_design_scores_gemma":[0.0004417445,0.00003288013,0.000496561,0.000008133095,0.000009352359,0.00003714536,0.001929486,0.9238204,0.00001156152,0.004320646,0.06857926,0.0003127904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798813,0.007370481,0.0006496627,0.0008835523,0.0002524562,0.0001503507,0.0003541246,0.0001004572,0.01035759],"genre_scores_gemma":[0.9975493,0.0004441262,0.0006343877,0.0007237413,0.0002486226,0.00002295356,0.00004881651,0.00004354893,0.0002845048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2157201,"threshold_uncertainty_score":0.9147182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05724344095002301,"score_gpt":0.2538789800020267,"score_spread":0.1966355390520037,"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."}}