{"id":"W4412128511","doi":"10.21105/joss.07471","title":"EcoLogits: Evaluating the Environmental Impacts of Generative AI","year":2025,"lang":"en","type":"article","venue":"The Journal of Open Source Software","topic":"Green IT and Sustainability","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Generative grammar; Computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001775341,0.0001057637,0.0002182577,0.00003809118,0.0001731487,0.00005635664,0.0007961107,0.00004236843,0.0001121531],"category_scores_gemma":[0.0003749221,0.00005537829,0.00008358821,0.0001242482,0.0001116969,0.0001806441,0.0002395207,0.000325774,0.000002516902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001515107,"about_ca_system_score_gemma":0.0000909769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002072068,"about_ca_topic_score_gemma":0.00001064359,"domain_scores_codex":[0.9989885,0.0002390745,0.0003634666,0.00005145739,0.000198235,0.0001592679],"domain_scores_gemma":[0.9990481,0.0004519297,0.0001511102,0.0002429638,0.00007164795,0.00003426287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0006419906,0.0002264639,0.1986566,0.000239678,0.00107261,0.00001417094,0.02924008,0.582478,0.01315346,0.0001589455,0.02243764,0.1516803],"study_design_scores_gemma":[0.00638105,0.002857213,0.8039755,0.0007277743,0.001405424,0.0002702613,0.06032447,0.04514658,0.04186064,0.0206531,0.01537645,0.001021603],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881708,0.0008866012,0.009457783,0.0008134997,0.000119877,0.0002885342,0.00000571653,0.00001233455,0.0002448544],"genre_scores_gemma":[0.9987193,0.00004397969,0.0006590923,0.0002375505,0.00004162378,0.000002955744,6.630637e-7,0.00001109586,0.0002837781],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6053188,"threshold_uncertainty_score":0.2258261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01647825900706613,"score_gpt":0.3055730702372558,"score_spread":0.2890948112301897,"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."}}