{"id":"W3200042178","doi":"10.33552/gjes.2020.04.000596","title":"SRIN: A New Dataset for Social Robot Indoor Navigation","year":2020,"lang":"en","type":"article","venue":"Global Journal of Engineering Sciences","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Western Canada Research Grid; Compute Canada","keywords":"The Internet; Computer science; Robot; Internet of Things; Computer security; Transport engineering; World Wide Web; Artificial intelligence; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005146941,0.003025406,0.001691906,0.002488452,0.001415445,0.000996666,0.003021867,0.002625189,0.01192985],"category_scores_gemma":[0.002290954,0.0004694432,0.001923566,0.003122293,0.0004650699,0.001279329,0.002179007,0.001889657,0.02377554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001161574,"about_ca_system_score_gemma":0.001908597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05967014,"about_ca_topic_score_gemma":0.1358455,"domain_scores_codex":[0.9988306,0.0002141172,0.000102912,0.0003749669,0.0003263637,0.0001510797],"domain_scores_gemma":[0.9991959,0.0001048807,0.00006791669,0.0002516553,0.0002819752,0.00009780106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005502892,0.0004133172,0.01021184,0.001836293,0.0003301551,0.0004664907,0.0002135245,0.005258005,0.002535559,0.001528268,0.8927517,0.08390461],"study_design_scores_gemma":[0.0003895104,0.0005078905,0.04333891,0.0008147071,0.0002832468,0.001239219,0.001239968,0.0362457,0.00776609,0.004392082,0.9034656,0.0003170822],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01686231,0.001901465,0.007394761,0.0004661132,0.0006799477,0.0003768276,0.9518922,0.01000854,0.01041785],"genre_scores_gemma":[0.01594943,0.0003401277,0.008614542,0.0001706833,0.00004749016,0.0003839204,0.9714935,0.0001769603,0.002823249],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05967014,"threshold_uncertainty_score":0.1186457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03587372869651002,"score_gpt":0.319697552224355,"score_spread":0.283823823527845,"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."}}