{"id":"W2913466723","doi":"10.3390/app9030470","title":"An Indoor Room Classification System for Social Robots via Integration of CNN and ECOC","year":2019,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Convolutional neural network; Artificial intelligence; Classifier (UML); Robot; Humanoid robot; Pattern recognition (psychology); Machine learning","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":[0.0002681953,0.0009093223,0.000451493,0.0006524859,0.0002994318,0.0003181066,0.0009410362,0.0005567393,0.001638526],"category_scores_gemma":[0.0005752385,0.0002383921,0.0003970689,0.0003745665,0.000209383,0.0006574644,0.0009358423,0.0004606333,0.0008751967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005324404,"about_ca_system_score_gemma":0.0005189726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01044527,"about_ca_topic_score_gemma":0.01683141,"domain_scores_codex":[0.999775,0.00001892881,0.000007542764,0.0000887897,0.00006113751,0.00004864254],"domain_scores_gemma":[0.999787,0.00002346559,0.00003009572,0.00003562328,0.0001018634,0.00002179452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004859019,0.0002900517,0.01659063,0.0001616674,0.0001691873,0.000687937,0.0001582371,0.05215105,0.07579958,0.001330822,0.01206412,0.8401108],"study_design_scores_gemma":[0.00002185255,0.0002394054,0.01484975,0.00004130355,0.0001066377,0.000300028,0.000153289,0.9356424,0.04039494,0.001461274,0.006737266,0.00005180883],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3230309,0.0009345576,0.6429244,0.0004959123,0.0005159092,0.0003070136,0.001208597,0.01549029,0.01509243],"genre_scores_gemma":[0.8286237,0.0002087222,0.1610745,0.000332023,0.0000659522,0.0001612074,0.001244602,0.0001303125,0.008159042],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01044527,"threshold_uncertainty_score":0.02076894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05374945286205018,"score_gpt":0.325780461708405,"score_spread":0.2720310088463548,"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."}}