{"id":"W2547426063","doi":"10.1109/icwcuca.2012.6402506","title":"Large-scale characterization of an underground mining environment for the 60 GHz frequency band","year":2012,"lang":"en","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"","keywords":"Path loss; Computer science; Frequency band; Wireless; Delay spread; Channel (broadcasting); Real-time computing; Range (aeronautics); Non-line-of-sight propagation; Electromagnetic environment; Software deployment; Electronic engineering; Scale (ratio); Radio propagation; Line-of-sight; Orthogonal frequency-division multiplexing; Remote sensing; Antenna (radio); Telecommunications; Engineering; Geology; Aerospace engineering; Physics","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":[0.0001853709,0.00006879633,0.00006940295,0.0000240373,0.00005492818,0.0000123171,0.00005153002,0.00003507214,0.0002079737],"category_scores_gemma":[0.000003631787,0.00005162911,0.00002759046,0.0000244172,0.000008192163,0.0002075363,0.000007403174,0.00002950687,0.000005977196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000020262,"about_ca_system_score_gemma":0.00000252994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002400394,"about_ca_topic_score_gemma":0.00000517424,"domain_scores_codex":[0.9995489,0.000009913111,0.0001521844,0.00006365427,0.00007149032,0.0001538729],"domain_scores_gemma":[0.999768,0.00002697002,0.00002602671,0.000128463,0.000009215071,0.00004132292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003969408,0.00005294431,0.0005061296,0.00005064933,0.0000329667,5.2359e-8,0.002481278,0.007860312,0.983662,0.0001269721,0.00001973468,0.005202961],"study_design_scores_gemma":[0.0004505572,0.00004897608,0.005364068,0.00001412052,0.00004748968,0.00000208242,0.0008769266,0.6674575,0.3217612,0.0001409015,0.003625545,0.0002106605],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4558413,0.00005935904,0.5434849,0.00001919153,0.00008995162,0.0001045149,0.000008092321,0.00002483144,0.0003678738],"genre_scores_gemma":[0.9900473,0.00005775376,0.009494877,0.00005243705,0.00009772581,0.00002671233,0.00005430393,0.00001830047,0.0001505708],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6619008,"threshold_uncertainty_score":0.2277166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02206619337723177,"score_gpt":0.2184028373264554,"score_spread":0.1963366439492236,"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."}}