{"id":"W8021931","doi":"10.1016/s1474-6670(17)32109-2","title":"Human presence detection and tracking for a concierge robot","year":2004,"lang":"en","type":"article","venue":"IFAC Proceedings Volumes","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Artificial intelligence; Computer science; Computer vision; Tracking (education); Robot; Psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.00007352218,0.0001121905,0.000111903,0.00006272678,0.0001508908,0.0001082333,0.00005379045,0.00007582975,0.000002562577],"category_scores_gemma":[0.00005152156,0.0001218528,0.00002938645,0.000108624,0.00003235078,0.0002387909,0.00000940441,0.00007104379,0.000001844093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005251712,"about_ca_system_score_gemma":0.000005988439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001959155,"about_ca_topic_score_gemma":0.00001660229,"domain_scores_codex":[0.9994046,9.406629e-7,0.0001463837,0.0001617535,0.00008925767,0.000197078],"domain_scores_gemma":[0.9997697,0.000009174139,0.00002874551,0.00003826183,0.00009755764,0.00005650044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000142705,0.00003428911,0.002467346,0.0006437855,0.00005058178,0.000001482898,0.001715933,0.2430436,0.7266465,0.006997864,0.0003039649,0.01808042],"study_design_scores_gemma":[0.001681158,0.0002888855,0.009245729,0.0001937971,0.00006075198,0.00002533092,0.0005302777,0.7103271,0.2691844,0.005534878,0.002295888,0.0006318871],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8357547,0.0001909601,0.1628354,0.00004850165,0.0001485542,0.0003059957,0.000002871451,0.0003236426,0.0003893733],"genre_scores_gemma":[0.9968498,0.00002169659,0.002876083,0.00001958733,0.0001035041,0.000032475,0.000002378906,0.00003097775,0.00006345597],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4672835,"threshold_uncertainty_score":0.4969011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01378921768415924,"score_gpt":0.2273025657737354,"score_spread":0.2135133480895762,"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."}}