{"id":"W4366150475","doi":"10.2139/ssrn.4420940","title":"Ecodynelec: Open Python Package to Create Historical Profiles of Environmental Impacts from Regional Electricity Mixes","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Python (programming language); Electricity; Open source; Computer science; R package; Environmental science; Engineering; Programming language; Electrical engineering; Software","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":[0.0005354051,0.001304141,0.0007133663,0.001483912,0.0005113329,0.001445792,0.001582779,0.000636052,0.07909442],"category_scores_gemma":[0.002665413,0.000948478,0.001679642,0.00124841,0.0003545445,0.001502535,0.001393462,0.001666785,0.0294242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005641954,"about_ca_system_score_gemma":0.001030204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006989788,"about_ca_topic_score_gemma":0.0144901,"domain_scores_codex":[0.9997914,0.0000259665,0.00001893719,0.00006111194,0.00006100746,0.00004146884],"domain_scores_gemma":[0.9993657,0.0002930393,0.00003989029,0.000133336,0.0001019696,0.00006598339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003327299,0.000246209,0.009584948,0.001668524,0.0004874602,0.0005782263,0.0006362237,0.05765237,0.005551105,0.01501,0.7892636,0.1189885],"study_design_scores_gemma":[0.0004916412,0.00006801424,0.01235864,0.0002466495,0.0001358494,0.0004924498,0.000207822,0.3666002,0.01558987,0.07198678,0.5315122,0.0003098961],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.01112934,0.0001466304,0.2253651,0.0002303803,0.0003061723,0.0001939572,0.1871559,0.558884,0.01658857],"genre_scores_gemma":[0.1342552,0.0005506316,0.3105076,0.0007472067,0.0001697875,0.001539268,0.278926,0.2429634,0.03034089],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.07909442,"threshold_uncertainty_score":0.2645972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01965201811693782,"score_gpt":0.2638380307998881,"score_spread":0.2441860126829503,"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."}}