{"id":"W4322806592","doi":"10.1061/joeedu.eeeng-7216","title":"Development of a Factorial Hypothetical Extraction Model for Analyzing Socioeconomic Environmental Effects of Carbon Emission Intensity Reduction","year":2023,"lang":"en","type":"article","venue":"Journal of Environmental Engineering","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Environmental economics; Robustness (evolution); Emission intensity; Environmental science; Factorial experiment; Electricity; Electricity generation; Intensity (physics); Greenhouse gas; Multi stage; Production (economics); Natural resource economics; Environmental engineering; Econometrics; Engineering; Process engineering; Mathematics; Statistics; Economics; Power (physics)","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":[0.00234558,0.001457686,0.001129782,0.001161467,0.0007435487,0.001156404,0.001478695,0.001639669,0.006971734],"category_scores_gemma":[0.002856629,0.0006066157,0.00246145,0.001172258,0.000589497,0.0008891891,0.0008925276,0.001116655,0.0003437678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00245741,"about_ca_system_score_gemma":0.002804444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02869588,"about_ca_topic_score_gemma":0.01790372,"domain_scores_codex":[0.9991519,0.0004421361,0.0000331908,0.0001535919,0.00007879196,0.0001402755],"domain_scores_gemma":[0.9983256,0.001260474,0.0001243368,0.00004079201,0.0002053961,0.00004326248],"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":[0.0002068631,0.0001379042,0.003016078,0.0001260297,0.0000735389,0.0001219387,0.00006198008,0.9837141,0.0009946763,0.00591795,0.0002690275,0.005360038],"study_design_scores_gemma":[0.00003743535,0.0001240263,0.0007657001,0.000007734709,0.00004989807,0.000008096788,0.0000376282,0.9967427,0.0002612353,0.001548452,0.0004030642,0.00001404393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3802809,0.0004759175,0.5972376,0.0004762405,0.0001134731,0.001567624,0.002966728,0.000562318,0.01631912],"genre_scores_gemma":[0.9160035,0.0003621979,0.07274274,0.00006784093,0.00001965014,0.003092237,0.001175687,0.0000272579,0.006508803],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02869588,"threshold_uncertainty_score":0.05705768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007892685968120415,"score_gpt":0.2201721056693987,"score_spread":0.2122794197012783,"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."}}