{"id":"W2330844409","doi":"10.1021/es302549d","title":"Predicting Project Environmental Performance under Market Uncertainties: Case Study of Oil Sands Coke","year":2013,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Carbon Management Canada","keywords":"Greenhouse gas; Natural gas; Life-cycle assessment; Net present value; Flexibility (engineering); Petroleum coke; Environmental economics; Present value; Investment (military); Carbon price; Production (economics); Environmental science; Natural resource economics; Coke; Economics; Waste management; Engineering; Finance; Microeconomics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"category_scores_codex":[0.0003997353,0.0002092479,0.0003535894,0.0009076544,0.0004158038,0.00004649688,0.0004914007,0.0001171958,0.001435941],"category_scores_gemma":[0.00001394603,0.0002045117,0.00007383187,0.0007839429,0.001586053,0.0005747722,0.0004058357,0.0001993635,0.0002096272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003744387,"about_ca_system_score_gemma":0.00001471554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001217321,"about_ca_topic_score_gemma":0.0000365434,"domain_scores_codex":[0.99814,0.00001248497,0.0005886664,0.0006517291,0.0001432715,0.000463897],"domain_scores_gemma":[0.9990497,0.00001942837,0.0003520736,0.0005027069,0.000003198651,0.00007288347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005705428,0.0007580323,0.9911422,0.000007757235,0.00005510106,0.00002835354,0.001526407,0.0001726526,0.002829873,0.0008181229,0.00005933761,0.002596485],"study_design_scores_gemma":[0.004312459,0.004603425,0.5619085,0.00004559667,0.0001480846,0.001219257,0.3052943,0.1019627,0.01071398,0.005182883,0.002552881,0.002055923],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963852,0.00104991,0.000008367001,0.00007988463,0.0001095218,0.0003068704,0.00003292052,0.0000488923,0.001978446],"genre_scores_gemma":[0.9974192,0.0008440774,0.0001424265,0.00003728954,0.00001808164,0.0001060945,0.000004389744,0.00001614296,0.001412282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4292337,"threshold_uncertainty_score":0.9994769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0138063651680127,"score_gpt":0.2024405275878124,"score_spread":0.1886341624197997,"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."}}