{"id":"W4389868623","doi":"10.51846/vol6iss2pp13-20","title":"Optimum Model for Tracking of Moving Objects","year":2023,"lang":"en","type":"article","venue":"Pakistan Journal of Engineering and Technology","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Non-line-of-sight propagation; Multilateration; Kalman filter; Computer science; Global Positioning System; Position (finance); Tracking (education); Noise (video); Algorithm; Standard deviation; Computer vision; Artificial intelligence; Wireless; Mathematics; Statistics; Telecommunications","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":[0.0008007837,0.001003154,0.001579026,0.0006568572,0.0003698173,0.001358038,0.001504356,0.00185851,0.004048527],"category_scores_gemma":[0.002294616,0.0005979579,0.000945252,0.001006071,0.0005912232,0.001569148,0.001035762,0.001680071,0.001910335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006627018,"about_ca_system_score_gemma":0.0008915149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006867803,"about_ca_topic_score_gemma":0.004845187,"domain_scores_codex":[0.9994106,0.000134576,0.00003185613,0.0002073656,0.0001414468,0.00007426464],"domain_scores_gemma":[0.9995901,0.0001519495,0.00007556692,0.00004072248,0.0001254472,0.00001621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007857678,0.00002376406,0.0006811268,0.0001420557,0.00003999638,0.00008452227,0.00006505527,0.9552527,0.001717138,0.01561791,0.001377143,0.02491989],"study_design_scores_gemma":[0.000005778518,0.00002656884,0.0001851848,0.00000918523,0.000009433788,0.00002718461,0.000007927337,0.9947761,0.0002400923,0.003282874,0.001422125,0.000007441988],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005265541,0.0005978995,0.9902011,0.0001718627,0.00008075828,0.00002718353,0.0001270355,0.0002679791,0.003260625],"genre_scores_gemma":[0.7942969,0.002938,0.1719962,0.0002240307,0.0003032442,0.0004351049,0.001072972,0.0002090242,0.02852443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006867803,"threshold_uncertainty_score":0.01365566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01142436851405821,"score_gpt":0.2399071338852462,"score_spread":0.228482765371188,"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."}}