{"id":"W2168454869","doi":"10.1109/icsens.2005.1597816","title":"Chest Sound Pick-Up Using a Multisensor Array","year":2006,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Focus (optics); Beamforming; Metric (unit); Computer science; Point (geometry); Acoustics; Algorithm; Engineering; Mathematics; Telecommunications; 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":[0.00008398999,0.0001015737,0.00009828446,0.00005676519,0.0001551342,0.0002996439,0.0003313004,0.00003789795,0.00002896962],"category_scores_gemma":[0.00001407098,0.00008676708,0.00004082375,0.0002445329,0.00003136755,0.0004391908,0.00005779184,0.00006546676,0.00008875156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003265826,"about_ca_system_score_gemma":0.00004550714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001703639,"about_ca_topic_score_gemma":0.00005036519,"domain_scores_codex":[0.9991342,0.00001247499,0.0001416265,0.0002721662,0.0001654172,0.0002740664],"domain_scores_gemma":[0.9995648,0.00002692503,0.00005186177,0.0002577371,0.00004653801,0.00005218982],"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":[0.000005776656,0.0001620397,0.0151345,0.00004738117,0.00001605994,0.00006257837,0.0005332676,0.0008075808,0.9141088,0.006060515,0.002060979,0.06100053],"study_design_scores_gemma":[0.0005036612,0.00001942349,0.005279904,0.00002406003,0.000005608713,0.00008379801,0.00004398495,0.01831852,0.9614061,0.01032828,0.003636012,0.0003506503],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2342972,0.00006494252,0.7556041,0.0002260009,0.0002261076,0.00004178532,2.414719e-7,0.0001871042,0.009352494],"genre_scores_gemma":[0.6294603,3.992348e-7,0.3685288,0.0002199758,0.0001317796,9.801324e-7,3.938236e-7,0.000005164354,0.001652181],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3951631,"threshold_uncertainty_score":0.3538259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02779448987402403,"score_gpt":0.2604409689740236,"score_spread":0.2326464790999996,"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."}}