{"id":"W4366721636","doi":"10.1002/aisy.202200284","title":"Energy in Robotics: An Interdisciplinary Challenge","year":2023,"lang":"en","type":"article","venue":"Advanced Intelligent Systems","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto; University of New Brunswick","funders":"","keywords":"Robot; Robotics; Artificial intelligence; Software deployment; Computer science; Metric (unit); Energy (signal processing); Matching (statistics); Human–computer interaction; Engineering; Operations management; Mathematics; Software engineering","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"],"consensus_categories":[],"category_scores_codex":[0.0002198831,0.0002705699,0.0003379183,0.0003581424,0.00006335787,0.000045988,0.0003660684,0.0001214919,0.00003466729],"category_scores_gemma":[0.000008704163,0.0002677004,0.00006907208,0.0005186515,0.00003119488,0.0002967859,0.0001203459,0.0001933941,0.0004008723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001474167,"about_ca_system_score_gemma":0.000009474952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005641008,"about_ca_topic_score_gemma":0.0001960519,"domain_scores_codex":[0.9982606,0.00005269588,0.0005611175,0.0003746084,0.0002230113,0.0005279776],"domain_scores_gemma":[0.9991964,0.0000565529,0.00004152342,0.0005162088,0.00004158897,0.0001476963],"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":[0.000007517161,0.00003580436,0.0000630915,0.0001016325,0.00001929293,0.00007286677,0.0008984856,0.9372007,0.0006646144,0.01205735,0.0002355712,0.04864314],"study_design_scores_gemma":[0.0001256394,0.000159479,0.00008837747,0.0002992008,0.000005342526,0.00001718817,0.002850364,0.9783151,0.003539133,0.003325487,0.01075475,0.0005199315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07714394,0.01143725,0.8613027,0.0002700615,0.01233922,0.00114017,0.00003229042,0.004231064,0.03210327],"genre_scores_gemma":[0.9963456,0.002197849,0.0002390238,0.00001298256,0.0001674119,0.0001054914,0.00004682706,0.00008334721,0.000801439],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9192017,"threshold_uncertainty_score":0.9999775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02764084665304784,"score_gpt":0.2887257755679852,"score_spread":0.2610849289149374,"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."}}