{"id":"W3025815279","doi":"10.3390/su12103977","title":"Costs and Benefits of Electrifying and Automating Bus Transit Fleets","year":2020,"lang":"en","type":"article","venue":"Sustainability","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":110,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Battery (electricity); Gallon (US); Diesel fuel; Total cost of ownership; Public transport; Metropolitan area; Transport engineering; Battery electric vehicle; Capital cost; Fleet management; Business; Environmental economics; Engineering; Automotive engineering; Power (physics); Economics; Waste management; Electrical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001126996,0.00008115011,0.0001384801,0.0000323711,0.00004218444,0.00001051171,0.00003155701,0.00004426954,0.00000774935],"category_scores_gemma":[0.0001630998,0.00008685057,0.00001843142,0.000228652,0.00004840634,0.00009539592,0.000004557602,0.00009522217,1.602388e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005593816,"about_ca_system_score_gemma":0.00003524216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000281402,"about_ca_topic_score_gemma":0.00003440135,"domain_scores_codex":[0.9994459,0.00001136532,0.0002169148,0.0001298471,0.00006954373,0.0001264626],"domain_scores_gemma":[0.9996112,0.00005219274,0.00001844989,0.00008099877,0.0001727198,0.00006444821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007461422,0.0001382977,0.5091877,0.007154082,0.0001721295,0.000007334875,0.0296642,0.04641172,0.01225483,0.05047966,0.00009466261,0.3443608],"study_design_scores_gemma":[0.0004703166,0.00005531209,0.9775439,0.00001456254,0.00002378017,0.000001245533,0.001005125,0.0152743,0.004479181,0.0007808253,0.0001999389,0.0001515158],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955441,0.0002135908,0.002636939,0.0009887749,0.00001436539,0.0002511447,0.00001562974,0.000188832,0.0001466068],"genre_scores_gemma":[0.9994571,0.00001288142,0.0004416724,0.00005438693,0.000006776595,0.00001067736,0.000005925167,0.000008563124,0.000001996261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4683562,"threshold_uncertainty_score":0.3541663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009944862717799784,"score_gpt":0.219699085355082,"score_spread":0.2097542226372822,"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."}}