{"id":"W4389990402","doi":"10.1016/j.asoc.2023.111136","title":"Advantage prioritization of digital carbon footprint awareness in optimized urban mobility using fuzzy Aczel Alsina based decision making","year":2023,"lang":"en","type":"article","venue":"Applied Soft Computing","topic":"Recycling and Waste Management Techniques","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Carbon footprint; Computer science; Ranking (information retrieval); Fuzzy logic; Environmental economics; Greenhouse gas; Operations research; Footprint; Artificial intelligence; Economics; Engineering","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":[0.002519941,0.001308524,0.001069001,0.002144492,0.001067939,0.003115361,0.00125735,0.001445142,0.00220295],"category_scores_gemma":[0.004536489,0.0004932927,0.001272496,0.001499699,0.001062914,0.00197217,0.001593456,0.001128318,0.0001472314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002515806,"about_ca_system_score_gemma":0.002351103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008182769,"about_ca_topic_score_gemma":0.00600723,"domain_scores_codex":[0.997826,0.0009483052,0.0001456213,0.0002969422,0.000546043,0.0002369765],"domain_scores_gemma":[0.9981883,0.001072759,0.0001693799,0.00004137239,0.0004272142,0.0001010006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001276228,0.00009497126,0.001690627,0.0001671414,0.00007631387,0.0001703308,0.0002841519,0.9304949,0.002517028,0.02549101,0.0004723092,0.03841356],"study_design_scores_gemma":[0.00001102403,0.0000584594,0.0001787446,0.00001795365,0.00001939786,0.00001676515,0.00008063151,0.9907373,0.0008249712,0.00756567,0.0004772823,0.00001181931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07707088,0.0002571891,0.9136978,0.0003727789,0.00004728741,0.0002442613,0.0000810303,0.00008637625,0.008142336],"genre_scores_gemma":[0.8706805,0.0002489501,0.1266484,0.00007596932,0.00002467664,0.0002898788,0.00008096322,0.00001360384,0.001937086],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008182769,"threshold_uncertainty_score":0.01825356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01795469255942455,"score_gpt":0.2883717224337398,"score_spread":0.2704170298743152,"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."}}