{"id":"W3035791417","doi":"10.3390/s20123543","title":"A Human Support Robot for the Cleaning and Maintenance of Door Handles Using a Deep-Learning Framework","year":2020,"lang":"en","type":"article","venue":"Sensors","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Robot; Task (project management); Automation; Process (computing); Mobile robot; Artificial intelligence; Computer science; Engineering; Simulation; Real-time computing; Embedded system; Systems engineering; Operating system; Mechanical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001788185,0.000519837,0.0003172416,0.0001664621,0.0002619667,0.0003452313,0.0009384208,0.0007846861,0.002175014],"category_scores_gemma":[0.0002807541,0.0002375116,0.0004538521,0.0001222632,0.0002970919,0.0003641449,0.0006835089,0.0007059577,0.0005065751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004075347,"about_ca_system_score_gemma":0.0009249291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006783176,"about_ca_topic_score_gemma":0.008670894,"domain_scores_codex":[0.9999001,0.00001039659,0.000003855139,0.00003277981,0.00002923892,0.00002363979],"domain_scores_gemma":[0.9999311,0.00001519489,0.000009986295,0.000008757636,0.00002251518,0.0000124385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001904002,0.0002474535,0.001706893,0.0001377866,0.0000786196,0.0002496718,0.0001111309,0.6190228,0.03862536,0.004760938,0.003269916,0.331599],"study_design_scores_gemma":[0.000006394694,0.00005835373,0.0002188483,0.00000511922,0.00000658437,0.00002106789,0.000006558731,0.9950912,0.002944874,0.0007998316,0.0008362766,0.000004795652],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03357903,0.0002811762,0.9601566,0.0002129619,0.00005183757,0.00006643848,0.00007320469,0.00261463,0.002963994],"genre_scores_gemma":[0.7074562,0.0002118458,0.2834164,0.0002214219,0.00002794484,0.0001776644,0.0002436571,0.00006727918,0.008177633],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006783176,"threshold_uncertainty_score":0.0134874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02317505975707986,"score_gpt":0.2441091062455228,"score_spread":0.2209340464884429,"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."}}