{"id":"W2095657844","doi":"10.1002/hbm.20043","title":"The effect of MR scanner noise on auditory cortex activity using fMRI","year":2004,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Hearing Loss and Rehabilitation","field":"Neuroscience","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research; Fondation Pour l'Audition","keywords":"Tonotopy; Loudness; Auditory cortex; Functional magnetic resonance imaging; Noise (video); Scanner; Auditory perception; Psychology; Audiology; Physics; Perception; Acoustics; Neuroscience; Medicine; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006827069,0.0001098021,0.0001390489,0.00007502232,0.0007410495,0.00004499533,0.0001494085,0.00005092159,0.000006842699],"category_scores_gemma":[0.0009171709,0.00007528948,0.00008232463,0.0001595798,0.0002382718,0.00009632851,0.00004304213,0.0001789843,0.00001460656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001192958,"about_ca_system_score_gemma":0.00003357889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006738831,"about_ca_topic_score_gemma":0.000003930444,"domain_scores_codex":[0.9988172,0.00028912,0.0001579728,0.0002640074,0.0002502891,0.000221425],"domain_scores_gemma":[0.9984083,0.001148098,0.0001107497,0.0002723302,0.00001692633,0.00004355029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00001807799,0.00002273456,0.0002373684,0.00005055725,0.000002389903,0.000002663155,0.0003855158,0.001737116,0.9952165,0.00107849,0.00005778577,0.001190769],"study_design_scores_gemma":[0.001089955,0.0006743216,0.7724503,0.0004130939,0.000008658218,0.000005603517,0.00006728495,0.001181054,0.2213357,0.001497641,0.001034324,0.0002419887],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976614,0.000005458538,0.0003383445,0.0004904038,0.0003740331,0.0002692046,0.000001242333,0.00004308358,0.0008168758],"genre_scores_gemma":[0.9994854,7.534516e-7,0.00003014616,0.0001229862,0.000181216,0.00000812592,2.208376e-7,0.00001400842,0.0001570833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7738808,"threshold_uncertainty_score":0.5699629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03598395681165095,"score_gpt":0.3024604394929514,"score_spread":0.2664764826813005,"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."}}