{"id":"W3094048071","doi":"10.1109/tnsre.2020.3032835","title":"Chirp Analyzer for Estimating Amplitude and Latency of Steady-State Auditory Envelope Following Responses","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","topic":"Hearing, Cochlea, Tinnitus, Genetics","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Fondo Nacional de Desarrollo Científico y Tecnológico; National Institute on Deafness and Other Communication Disorders","keywords":"Chirp; Amplitude; Spectrum analyzer; Envelope (radar); Acoustics; Latency (audio); Physics; Steady state (chemistry); Audiology; Computer science; Telecommunications; Optics; Medicine","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":[0.000893986,0.0006207674,0.0002373819,0.001062424,0.0001795302,0.0004990619,0.0004301587,0.0007766514,0.001799758],"category_scores_gemma":[0.003707087,0.0001647415,0.0001736748,0.0006827436,0.0002897774,0.0006073169,0.000398159,0.0003461123,0.0005682603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002691289,"about_ca_system_score_gemma":0.0004669264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001520542,"about_ca_topic_score_gemma":0.002582681,"domain_scores_codex":[0.9995674,0.0001115306,0.00002301865,0.00009107745,0.000193333,0.00001366611],"domain_scores_gemma":[0.9985189,0.0008169106,0.0001439686,0.0001181812,0.0003560119,0.00004609661],"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":[0.0008566435,0.00008950666,0.008145967,0.0005193666,0.0001143533,0.0004709174,0.0001188796,0.01112931,0.3855634,0.002539925,0.002301721,0.5881501],"study_design_scores_gemma":[0.0001179135,0.0006797824,0.04022862,0.0001372459,0.0002150039,0.002262628,0.0001159134,0.7563417,0.1883696,0.002529837,0.008883215,0.0001184965],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07447047,0.001014899,0.9205946,0.00008767467,0.00009863453,0.0001567496,0.0004197339,0.001304521,0.001852741],"genre_scores_gemma":[0.3350731,0.0006345599,0.6619529,0.00009130601,0.00006671827,0.0001816135,0.0004137696,0.0001260913,0.001459873],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001799758,"threshold_uncertainty_score":0.006020784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02701370794069149,"score_gpt":0.2636041539297028,"score_spread":0.2365904459890113,"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."}}