{"id":"W4406278433","doi":"10.2139/ssrn.5093875","title":"Environmental Bonds and Public Liability for Resource Extraction Site Cleanup","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Liability; Extraction (chemistry); Resource (disambiguation); Business; Bond; Environmental science; Computer science; Chemistry; Finance; Organic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00254677,0.00031857,0.0007025552,0.001390429,0.0009862577,0.003041403,0.0008712673,0.005351394,0.01763476],"category_scores_gemma":[0.02564682,0.0005789906,0.0006430347,0.001386806,0.001707212,0.004196467,0.001641456,0.003663412,0.001027986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002166557,"about_ca_system_score_gemma":0.00154155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008641562,"about_ca_topic_score_gemma":0.009943786,"domain_scores_codex":[0.9987792,0.000313507,0.0001031445,0.0001664225,0.0002048631,0.0004327828],"domain_scores_gemma":[0.9734423,0.01415426,0.007791793,0.001125378,0.001524372,0.001961828],"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":[0.001187035,0.0006724896,0.1582482,0.0002183229,0.0002322068,0.001701632,0.0007348196,0.1026999,0.001269114,0.6702779,0.03086148,0.03189696],"study_design_scores_gemma":[0.0001298436,0.0003456061,0.06634201,0.0001415002,0.0002812741,0.0007107616,0.001698499,0.1379631,0.001496457,0.7789083,0.01187034,0.0001122581],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9012647,0.00294235,0.0219897,0.01835723,0.0002773931,0.00004783887,0.002071383,0.0002448471,0.05280446],"genre_scores_gemma":[0.9886352,0.0005558315,0.0002748831,0.0001784259,0.0001483343,0.00001111022,0.0003320076,0.00002497821,0.009839362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01763476,"threshold_uncertainty_score":0.05899411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04278551647979818,"score_gpt":0.2555190276936554,"score_spread":0.2127335112138572,"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."}}