{"id":"W4377241494","doi":"10.1007/s10098-023-02537-9","title":"Carbon emissions pinch analysis (CEPA) for emissions reduction and energy planning in Canada","year":2023,"lang":"en","type":"article","venue":"Clean Technologies and Environmental Policy","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Greenhouse gas; Pinch analysis; Electricity; Renewable energy; Work (physics); Environmental economics; Natural resource economics; Reduction (mathematics); Environmental science; Business; Environmental engineering; Engineering; Economics; Process integration; Process engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0000402386,0.0001774626,0.0002346462,0.0006466853,0.00005209284,0.0000137962,0.0001353333,0.0001754043,0.000001725903],"category_scores_gemma":[0.00005967639,0.0001768833,0.00003840741,0.0007593888,0.0001383638,0.00004195218,0.0002124062,0.0001620759,1.348111e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004607957,"about_ca_system_score_gemma":0.0000247617,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1187065,"about_ca_topic_score_gemma":0.1158675,"domain_scores_codex":[0.9991252,0.000004736412,0.0001834238,0.0002598089,0.0000832942,0.0003435356],"domain_scores_gemma":[0.9996187,0.00004120203,0.00002967736,0.0002597283,0.000001382871,0.00004929491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001612209,0.00001730305,0.01979673,0.00007756885,0.000270779,0.00003746478,0.0002806134,0.03526402,0.0736533,0.0009562966,0.005236471,0.8643934],"study_design_scores_gemma":[0.001422192,0.0001712367,0.1388314,0.0001723888,0.0003656826,0.0000929362,0.4322598,0.2991219,0.1058816,0.01046479,0.009347153,0.001869002],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967053,0.001094954,0.00004794829,0.0006462656,0.00004556992,0.00008251283,0.00005209938,0.001152943,0.0001723996],"genre_scores_gemma":[0.9971415,0.00248318,0.0001311034,0.00001228573,0.00002166076,0.00006325216,0.00003817816,0.00002596075,0.00008291237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8625243,"threshold_uncertainty_score":0.9002656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007971075224655068,"score_gpt":0.2054128367412573,"score_spread":0.1974417615166022,"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."}}