{"id":"W2610995270","doi":"","title":"The electric vehicle routing problem with partial charge, nonlinear charging function, and capacitated charging stations","year":2017,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Solver; Electric vehicle; Vehicle routing problem; Charging station; Mathematical optimization; Computer science; Nonlinear system; Routing (electronic design automation); Function (biology); Charge (physics); Iterated function; Mathematics; Power (physics); Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.002007507,0.0003397521,0.0002826643,0.0001246274,0.001486408,0.0008731984,0.0005948847,0.0001948671,0.00002186139],"category_scores_gemma":[0.0002690744,0.0002821723,0.00007356834,0.0002906742,0.0001281834,0.0002044919,0.0002390143,0.001004711,0.000009716406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001074065,"about_ca_system_score_gemma":0.0001515269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002883975,"about_ca_topic_score_gemma":0.0003712498,"domain_scores_codex":[0.9976464,0.0006593513,0.0004004205,0.0004760484,0.0002981602,0.0005196321],"domain_scores_gemma":[0.9971226,0.0004504711,0.0003432815,0.00106894,0.0008745113,0.0001401283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001939328,0.0005730887,0.05266966,0.001984112,0.002344013,0.0000284068,0.04963538,0.01906606,0.1159761,0.1966344,0.004191396,0.5567034],"study_design_scores_gemma":[0.0007743479,0.00000188728,0.01029081,0.001114262,0.0001110153,0.00001918617,0.0001227208,0.9450727,0.02866867,0.002679459,0.01046297,0.0006819371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8531342,0.004318297,0.1175446,0.005875556,0.0003710508,0.00119635,0.00008695616,0.001004153,0.01646886],"genre_scores_gemma":[0.9909286,0.001107756,0.006402761,0.00002782121,0.0000751034,0.00009377834,0.0001890893,0.000081536,0.001093501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9260067,"threshold_uncertainty_score":0.999963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007616192923670329,"score_gpt":0.1958815564179499,"score_spread":0.1882653634942796,"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."}}