{"id":"W20473166","doi":"10.1097/mcp.0b013e32833b1c6c","title":"Implementing a Cellular Positioning System: Low-cost Alternative to Global Positioning System.","year":2005,"lang":"en","type":"article","venue":"International Conference on Wireless Networks","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Hybrid positioning system; Positioning system; Computer science; Global Positioning System; Precise Point Positioning; Embedded system; Engineering; Telecommunications; GNSS applications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007189004,0.0007685676,0.0003903844,0.0006279509,0.0003525142,0.0008222117,0.00119547,0.001247806,0.01272887],"category_scores_gemma":[0.002180591,0.0002008806,0.0003726287,0.0006810462,0.0001959682,0.0009101103,0.0009260945,0.0004763142,0.007985894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004628609,"about_ca_system_score_gemma":0.0008345899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006706052,"about_ca_topic_score_gemma":0.007613417,"domain_scores_codex":[0.9992281,0.0002939887,0.0000298135,0.0001048433,0.0002505283,0.00009272218],"domain_scores_gemma":[0.999084,0.0001820207,0.00008406416,0.000226598,0.000351286,0.00007194346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006653017,0.0001585152,0.01611971,0.0003052027,0.000211055,0.0003461483,0.0001136727,0.02606258,0.01923458,0.01065585,0.03301098,0.8931164],"study_design_scores_gemma":[0.0005341597,0.00246159,0.03266173,0.0002767463,0.0007780908,0.002396356,0.0004991515,0.4848116,0.03660138,0.02472411,0.4140137,0.0002413389],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08836826,0.00574398,0.8169107,0.009496649,0.003327164,0.0005501876,0.001975876,0.01590552,0.05772159],"genre_scores_gemma":[0.6964924,0.001974487,0.2648941,0.001317027,0.0006362764,0.0002245091,0.002101229,0.0001908221,0.03216906],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01272887,"threshold_uncertainty_score":0.04258233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03032044847013917,"score_gpt":0.3169485323089805,"score_spread":0.2866280838388413,"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."}}