{"id":"W4318711404","doi":"10.1007/978-3-031-24667-8_4","title":"AR Point &amp;Click: An Interface for Setting Robot Navigation Goals","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Headset; Computer science; Interface (matter); Robot; Augmented reality; Human–computer interaction; Point (geometry); Gesture; Set (abstract data type); User interface; Mobile robot; Mobile robot navigation; Computer vision; Artificial intelligence; Robot control; Operating system; Programming language","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":[0.0004427445,0.001596052,0.0007049523,0.0006108548,0.0003701108,0.00101788,0.001662182,0.001926934,0.1186037],"category_scores_gemma":[0.001753641,0.00046908,0.0003997034,0.0004260886,0.0002943402,0.001492228,0.00160138,0.0008733748,0.0404197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001914589,"about_ca_system_score_gemma":0.0002521802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00109452,"about_ca_topic_score_gemma":0.002188441,"domain_scores_codex":[0.9997901,0.00003074204,0.00001210461,0.00003731074,0.0001055835,0.00002412446],"domain_scores_gemma":[0.9991558,0.0005204548,0.00002941111,0.00006277812,0.0001405339,0.00009102136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002547176,0.0002928854,0.001098807,0.000883125,0.00004471891,0.001361677,0.001107254,0.002044002,0.1242401,0.009179838,0.287046,0.5701545],"study_design_scores_gemma":[0.0008431686,0.001228404,0.00881389,0.0006591935,0.00022352,0.004569862,0.0006413517,0.1044323,0.1254216,0.01154502,0.7411346,0.0004869519],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01750483,0.0008267513,0.7951993,0.0002762341,0.0006461502,0.000311439,0.002601852,0.1173892,0.06524432],"genre_scores_gemma":[0.1719713,0.001311661,0.5344568,0.001631166,0.0003058943,0.001339982,0.006434706,0.02170583,0.2608427],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1186037,"threshold_uncertainty_score":0.3967689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02886314099213583,"score_gpt":0.3049990271546153,"score_spread":0.2761358861624795,"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."}}