{"id":"W4393410366","doi":"10.2139/ssrn.4746446","title":"Carbon Footprint Measurement and Mitigation Using AI","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wycliffe College","funders":"","keywords":"Carbon footprint; Footprint; Environmental science; Carbon fibers; Environmental resource management; Engineering; Greenhouse gas; Computer science; Geography; Geology; Archaeology; Oceanography; Algorithm","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":[0.0008475452,0.0006149362,0.0004758888,0.002379315,0.0004935074,0.001810477,0.0005917061,0.0005567892,0.004457742],"category_scores_gemma":[0.001845468,0.0001876659,0.0004667415,0.003371284,0.0004164861,0.001892291,0.000716315,0.0005754752,0.0008080513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007001737,"about_ca_system_score_gemma":0.0005137787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005578862,"about_ca_topic_score_gemma":0.006817039,"domain_scores_codex":[0.9990915,0.0002106439,0.00003615806,0.0001512498,0.0004478355,0.00006256197],"domain_scores_gemma":[0.999112,0.0003602788,0.00008665033,0.000152595,0.0002590772,0.00002938109],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007290832,0.0005252912,0.0354955,0.0008278454,0.0004739785,0.0001807668,0.0001947565,0.1608119,0.06155074,0.04472404,0.00555702,0.6889291],"study_design_scores_gemma":[0.00004575662,0.0002650645,0.02315694,0.0001037656,0.000187089,0.00016269,0.0003420018,0.8463976,0.06733848,0.04138782,0.0205017,0.0001110696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.253359,0.002991341,0.5571681,0.0009826397,0.0006207149,0.0002909479,0.002963261,0.004498949,0.177125],"genre_scores_gemma":[0.8963933,0.0007700988,0.096118,0.0001096322,0.00006934417,0.00008582589,0.0006790763,0.0000891804,0.005685638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005578862,"threshold_uncertainty_score":0.01491261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009010964058527896,"score_gpt":0.240341591407486,"score_spread":0.2313306273489581,"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."}}