{"id":"W4385824761","doi":"10.1016/j.erss.2023.103246","title":"Corrigendum to “Pluralizing energy justice: Incorporating feminist, anti-racist, Indigenous, and postcolonial perspectives” [Energy Research & Social Science, Volume 97, March 2023, 102996]","year":2023,"lang":"en","type":"erratum","venue":"Energy Research & Social Science","topic":"Energy and Environment Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Indigenous; Social justice; Sociology; Volume (thermodynamics); Energy (signal processing); Gender studies; Environmental ethics; Political science; Social science; Physics; Ecology; Philosophy; Thermodynamics; Biology","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":[0.004382314,0.002478257,0.002674036,0.002832373,0.0128273,0.01124238,0.005251453,0.02372055,0.06619936],"category_scores_gemma":[0.02604486,0.001363907,0.002759056,0.002686117,0.004129775,0.004013959,0.003160087,0.02176048,0.04600887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01268239,"about_ca_system_score_gemma":0.01695521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.231883,"about_ca_topic_score_gemma":0.3999015,"domain_scores_codex":[0.9930442,0.0008179201,0.0007336594,0.001122847,0.003412668,0.0008688036],"domain_scores_gemma":[0.9840522,0.003858316,0.0004384962,0.0007239308,0.01001103,0.0009160035],"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":[0.000006086588,0.000005924627,0.00001760971,0.00002417007,0.000002101257,0.00003258747,0.0000186132,0.00001297594,0.00001221195,0.0009145665,0.9978465,0.001106799],"study_design_scores_gemma":[0.00002337873,0.0000166016,0.001116071,0.0002046388,0.00002148219,0.00004813385,0.0002359403,0.0001734296,0.0001118805,0.002942772,0.995052,0.00005367467],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0002439103,0.002436509,0.0004594832,0.2577987,0.679572,0.0001174885,0.001662676,0.0005745216,0.05713467],"genre_scores_gemma":[0.002904365,0.002273362,0.0008897122,0.379743,0.06776344,0.0003652268,0.0007783853,0.0004473976,0.5448351],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.231883,"threshold_uncertainty_score":0.4610665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07967580900865963,"score_gpt":0.3790265140005168,"score_spread":0.2993507049918572,"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."}}