{"id":"W2127473114","doi":"10.1109/melcon.2006.1653111","title":"UWB Positioning Using Six-port Technology and a Learning Machine","year":2006,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Multipath propagation; Computer science; Ranging; Robustness (evolution); Positioning system; Signal processing; Rake receiver; Wideband; Impulse response; Real-time computing; Electronic engineering; Channel (broadcasting); Engineering; Telecommunications; Node (physics); Radar","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":[0.0005318241,0.0004435754,0.0004972559,0.0006452525,0.0002279233,0.0005950678,0.0006253792,0.000763631,0.001359535],"category_scores_gemma":[0.00146966,0.0002540634,0.0003801909,0.0005379779,0.000292369,0.001001209,0.0004530952,0.0005208749,0.0006936392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002109508,"about_ca_system_score_gemma":0.0002394959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005671032,"about_ca_topic_score_gemma":0.0004392021,"domain_scores_codex":[0.9995926,0.0001190251,0.00003316411,0.00007745142,0.0001522714,0.00002553385],"domain_scores_gemma":[0.9994758,0.000205092,0.00007046555,0.00008256686,0.0001464557,0.00001975845],"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":[0.000289635,0.0001195863,0.002472775,0.0001596446,0.0001022209,0.0001519797,0.00009736713,0.0931008,0.05239626,0.00936018,0.00101831,0.8407313],"study_design_scores_gemma":[0.0000230567,0.0003225162,0.001266691,0.00001528727,0.00003390486,0.0003318644,0.0000231702,0.9611186,0.02915465,0.003189142,0.004485386,0.00003565929],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01401744,0.0001187521,0.9844373,0.00004817047,0.00003081331,0.0000158144,0.00001226082,0.0006637879,0.0006557956],"genre_scores_gemma":[0.3354357,0.0003177936,0.6611099,0.00006234146,0.00006309052,0.00008292926,0.0001015546,0.00003356821,0.002793113],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001359535,"threshold_uncertainty_score":0.004548073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003880898319716173,"score_gpt":0.1904616452394089,"score_spread":0.1865807469196928,"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."}}