{"id":"W2103556919","doi":"10.1109/vtcf.2006.586","title":"Performance Analysis and Implementation of a New Position Location System Using DTV TxID Watermark","year":2006,"lang":"en","type":"article","venue":"IEEE Vehicular Technology Conference","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Communications Research Centre Canada","funders":"","keywords":"Computer science; Synchronization (alternating current); Transmitter; Global Positioning System; Watermark; Digital television; Position (finance); Positioning system; Digital watermarking; Real-time computing; Digital Video Broadcasting; Electronic engineering; Computer hardware; Telecommunications; Computer vision; Engineering","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":[0.00006972713,0.0001325427,0.0002252005,0.0006980616,0.0000650634,0.00001995697,0.0001239268,0.0002160948,0.000006523115],"category_scores_gemma":[0.000002817603,0.0001342626,0.00003218793,0.001118983,0.00008877561,0.0001320057,0.00002048391,0.00009471423,0.000002630777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008246079,"about_ca_system_score_gemma":0.00003083656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003303273,"about_ca_topic_score_gemma":0.0001126404,"domain_scores_codex":[0.9992428,0.00001084787,0.0002989466,0.0001678957,0.0001055243,0.000173989],"domain_scores_gemma":[0.9995373,0.000005409113,0.00008589208,0.0002161756,0.0001388942,0.00001632727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001124813,0.000022201,0.2169918,0.0006669906,0.0004454172,0.0000109699,0.0002284486,0.1516398,0.5865695,0.01104195,0.0000625656,0.032309],"study_design_scores_gemma":[0.0002238087,0.00002714832,0.01539831,0.00004983717,0.0002065831,0.00001728286,0.0003619145,0.3377775,0.6456099,0.0001770392,0.00001498006,0.000135718],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7516986,0.0001174915,0.2474402,0.00003278174,0.00004853779,0.0001211334,0.000004362806,0.0004930276,0.00004379793],"genre_scores_gemma":[0.9977214,0.00004300995,0.002158278,0.000002896931,0.00001408669,0.00001234021,0.00003022402,0.00001125208,0.000006553914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2460227,"threshold_uncertainty_score":0.5475072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007274953324818901,"score_gpt":0.2198415859337173,"score_spread":0.2125666326088984,"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."}}