{"id":"W3093297645","doi":"10.3390/su12208541","title":"Investigating the Impact of Energy Source Level on the Self-Guided Vehicle System Performances, in the Industry 4.0 Context","year":2020,"lang":"en","type":"article","venue":"Sustainability","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Battery (electricity); Context (archaeology); State of charge; Trajectory; Path (computing); Automotive engineering; Energy (signal processing); Motion planning; Simulation; Engineering; Computer science; Transport engineering; Power (physics); Artificial intelligence; Robot; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002900903,0.0003275431,0.0002238164,0.0002528713,0.0001732014,0.000477848,0.0002710241,0.000287808,0.0009526554],"category_scores_gemma":[0.001811092,0.00009160478,0.0001749681,0.0002626792,0.0001754291,0.0007024345,0.0003220605,0.0002389838,0.0001665544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002433147,"about_ca_system_score_gemma":0.0003037977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00189666,"about_ca_topic_score_gemma":0.002853648,"domain_scores_codex":[0.9998821,0.00002613038,0.000006908258,0.00002681135,0.00003799375,0.00001996774],"domain_scores_gemma":[0.9993157,0.0004540108,0.00004560167,0.00004359304,0.0001248361,0.00001622768],"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":[0.0003411536,0.0001443634,0.01139321,0.0005745269,0.0001134408,0.0001428329,0.0001108502,0.8295093,0.04230008,0.001576242,0.0004833519,0.1133108],"study_design_scores_gemma":[0.00001706206,0.00207316,0.02201362,0.00006585094,0.0001284342,0.000204003,0.0003838168,0.886643,0.08227666,0.003131768,0.003023465,0.00003924882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9221534,0.001241428,0.07065093,0.0001428237,0.00003489869,0.00003334534,0.0001816424,0.0002060372,0.005355583],"genre_scores_gemma":[0.9948962,0.000219953,0.004312831,0.000008569047,0.000002014531,0.000009074382,0.00009034767,0.00001323729,0.000447732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00189666,"threshold_uncertainty_score":0.003771305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05323945687362235,"score_gpt":0.2864486320426742,"score_spread":0.2332091751690518,"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."}}