{"id":"W2893062876","doi":"10.5194/isprs-archives-xlii-1-379-2018","title":"EVALUATION OF DYNAMIC AD-HOC UWB INDOOR POSITIONING SYSTEM","year":2018,"lang":"en","type":"article","venue":"˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Firmware; Node (physics); Computer science; Positioning system; Transceiver; Ultra-wideband; Multilateration; Indoor positioning system; Wireless ad hoc network; Real-time computing; Dynamic positioning; Range (aeronautics); Wireless; Engineering; Computer hardware; Telecommunications; Aerospace 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.002204437,0.0003842687,0.0004171633,0.001095145,0.001082434,0.0004640798,0.001426269,0.0001213083,0.000009407659],"category_scores_gemma":[0.000712696,0.0002574529,0.0003009217,0.001112152,0.003192342,0.0004921908,0.0005981951,0.000360155,0.000004188595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001112376,"about_ca_system_score_gemma":0.0002270495,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.314806,"about_ca_topic_score_gemma":0.102316,"domain_scores_codex":[0.9950486,0.0002927026,0.001486885,0.0003175804,0.002405682,0.0004485189],"domain_scores_gemma":[0.9968233,0.0005662613,0.001274663,0.0004792385,0.0007564895,0.0001001216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007728132,0.00001077775,0.0000773318,0.00006831232,0.0001133032,1.306075e-7,0.003003196,0.007802776,0.003647831,0.00001445932,0.0000264894,0.9851581],"study_design_scores_gemma":[0.0007648682,0.000146329,0.002070711,0.0005255931,0.00009065991,0.0001007362,0.003550943,0.9647735,0.02321793,0.003540181,0.0009470235,0.0002714896],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03165736,0.0000839632,0.9525861,0.0009625648,0.00221819,0.0007028467,0.0001057247,0.0001245637,0.01155867],"genre_scores_gemma":[0.9964154,0.0001570313,0.002996437,0.0002531954,0.00009698421,6.404734e-7,0.00003828102,0.00001481641,0.00002718546],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9848866,"threshold_uncertainty_score":0.9999878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01477802167380704,"score_gpt":0.2535475844525786,"score_spread":0.2387695627787716,"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."}}