{"id":"W2254408903","doi":"10.1088/1748-9326/10/12/124017","title":"Characterizing the GHG emission impacts of carsharing: a case of Vancouver","year":2015,"lang":"en","type":"article","venue":"Environmental Research Letters","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"University of British Columbia; Transport Canada; National Science Foundation","keywords":"Greenhouse gas; TRIPS architecture; Train; Public transport; Transport engineering; Business; Car sharing; Service (business); Environmental economics; Economics; Marketing; Engineering; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004358098,0.00006066155,0.00007742929,0.00008307617,0.00004129433,0.00000601327,0.0001005746,0.00002600579,0.00005738885],"category_scores_gemma":[0.00002981436,0.00004814064,0.00003051158,0.000142822,0.0001494235,0.0001017339,0.00002346695,0.000189301,0.000006702224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001052781,"about_ca_system_score_gemma":0.00001211112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009448317,"about_ca_topic_score_gemma":0.00004924701,"domain_scores_codex":[0.9992205,0.00003386102,0.0001889344,0.0000802639,0.0003045033,0.0001719578],"domain_scores_gemma":[0.9996272,0.00005676891,0.00002436595,0.0002003476,0.00001008081,0.00008121597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000133307,0.00004059267,0.009284596,0.00003705878,0.00002281889,0.00004848445,0.003059208,0.0007037133,0.9826901,0.00001935261,0.003027312,0.001053432],"study_design_scores_gemma":[0.001318095,0.0001456504,0.1361371,0.0001086053,0.0000232655,0.00007132079,0.01044761,0.002415569,0.8340729,0.00005969972,0.01491632,0.0002837696],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990562,0.0000452781,0.0001140809,0.0002629375,0.00007727716,0.0001561435,0.0000342493,0.00001548797,0.000238375],"genre_scores_gemma":[0.9997482,0.00001324571,0.00008417589,0.00006402034,0.00001827395,0.00001240978,0.00001451532,0.00001219874,0.00003301505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1486171,"threshold_uncertainty_score":0.1963118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04658413952474841,"score_gpt":0.3000343622897437,"score_spread":0.2534502227649953,"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."}}