{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000134913,0.0001034927,0.0001403147,0.0003658618,0.00003071466,0.0001014978,0.0001414246,0.00004519507,0.0000449903],"category_scores_gemma":[0.0007381407,0.0001120663,0.0000285184,0.0001906212,0.00002116006,0.0002807425,0.00009582502,0.0003352663,0.000002128349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002567107,"about_ca_system_score_gemma":0.00006167408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002375218,"about_ca_topic_score_gemma":0.000001549622,"domain_scores_codex":[0.9991661,0.000009635987,0.0002264629,0.00008427303,0.0002533254,0.0002601471],"domain_scores_gemma":[0.9989468,0.0001813383,0.000045833,0.00009219408,0.0006730161,0.00006084174],"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":[0.00001244637,0.00002725119,0.0004834431,0.0001305377,0.0002748389,0.007439693,0.0001837833,0.8805857,0.09715242,0.005121193,0.00212968,0.006458974],"study_design_scores_gemma":[0.002697868,0.0003008183,0.005149966,0.0003698677,0.00007322146,0.006242864,0.004539445,0.4697517,0.4163139,0.02051811,0.07291083,0.001131492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6997136,0.003951455,0.2905225,0.00396295,0.001008271,0.0001431257,0.00001446417,0.0002782017,0.0004054322],"genre_scores_gemma":[0.99433,0.001095379,0.004067366,0.00007173717,0.0001220425,0.000004372513,0.000001714725,0.0000247419,0.0002825692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4108341,"threshold_uncertainty_score":0.4569932,"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."}}