{"id":"W2141096089","doi":"10.1109/iembs.2009.5333107","title":"Detecting regional lung properties using audio transfer functions of the respiratory system","year":2009,"lang":"en","type":"article","venue":"","topic":"Phonocardiography and Auscultation Techniques","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Imaging phantom; Transfer function; Acoustics; SIGNAL (programming language); Computer science; Additive white Gaussian noise; Signal processing; Noise (video); White noise; Physics; Engineering; Artificial intelligence; Telecommunications; Digital signal processing; Optics; Electrical engineering; Computer hardware","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":[0.0004342797,0.0004235697,0.0002609369,0.0006060214,0.00009068238,0.0003710314,0.00030905,0.0006436307,0.001036746],"category_scores_gemma":[0.001793404,0.0001338022,0.0001911502,0.0002120042,0.0002485993,0.0006962463,0.0002463049,0.0002285882,0.0003836676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001129307,"about_ca_system_score_gemma":0.0001153601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002247551,"about_ca_topic_score_gemma":0.0002830682,"domain_scores_codex":[0.9998423,0.00004175517,0.000005588309,0.00003731145,0.00005855434,0.00001452501],"domain_scores_gemma":[0.9995313,0.0003003231,0.00004669876,0.00003339706,0.00006489598,0.00002338712],"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":[0.0004726552,0.00007021279,0.007494212,0.0002511232,0.00004587577,0.0002793132,0.0001251185,0.005508859,0.8234183,0.0002650736,0.0001494015,0.16192],"study_design_scores_gemma":[0.00008473753,0.00235249,0.06921503,0.0000591151,0.0003005378,0.00364026,0.0002371574,0.1038498,0.8158383,0.000965283,0.003326122,0.0001311352],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6419836,0.001647222,0.3532796,0.000109881,0.00005703965,0.00008682706,0.0001663455,0.0009752584,0.001694343],"genre_scores_gemma":[0.9392083,0.0006039861,0.05898102,0.00006469559,0.00005041565,0.00004531123,0.00007584252,0.00003877874,0.000931792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001036746,"threshold_uncertainty_score":0.003468215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.052133962394611,"score_gpt":0.2669941762211823,"score_spread":0.2148602138265713,"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."}}