{"id":"W3121683905","doi":"10.1080/19397038.2020.1856968","title":"Electric vehicle battery state changes and reverse logistics considerations","year":2021,"lang":"en","type":"article","venue":"International Journal of Sustainable Engineering","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Battery (electricity); Scarcity; Electric vehicle; Automotive industry; Environmental economics; Battery capacity; Reverse logistics; Supply chain; Automotive engineering; Business; Computer science; Power (physics); Engineering; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004512977,0.0002927417,0.0002966752,0.0004968825,0.0003684031,0.00125916,0.0007064134,0.0008212783,0.004485658],"category_scores_gemma":[0.002200177,0.0002147155,0.0007079098,0.0004488907,0.000505926,0.002409885,0.0004843428,0.0006651848,0.0004169497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001345953,"about_ca_system_score_gemma":0.0007302591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01151823,"about_ca_topic_score_gemma":0.01069599,"domain_scores_codex":[0.9997349,0.00006337761,0.0000108049,0.00005601093,0.00007523048,0.00005966638],"domain_scores_gemma":[0.9992119,0.0003952257,0.00008920171,0.00005352354,0.000228618,0.00002154689],"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":[0.0001206808,0.00007417538,0.01061262,0.0001917727,0.00004153603,0.0008930853,0.0002130163,0.8422955,0.004190102,0.1004887,0.003339389,0.03753942],"study_design_scores_gemma":[0.000006086898,0.0001252274,0.004220666,0.00005205682,0.00004751908,0.0004346266,0.0004438951,0.9311277,0.003476204,0.04843361,0.01159093,0.00004148792],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5941534,0.006407191,0.2825375,0.006853989,0.000392879,0.0001139565,0.002768557,0.0003752137,0.1063973],"genre_scores_gemma":[0.9857981,0.00123038,0.00326491,0.0001092295,0.00002771046,0.00001903403,0.0002765461,0.00002680398,0.009247352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01151823,"threshold_uncertainty_score":0.02290237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01049900181619911,"score_gpt":0.2431417817852121,"score_spread":0.232642779969013,"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."}}