{"id":"W4389665176","doi":"10.2196/49969","title":"Cross-Modal Sensory Boosting to Improve High-Frequency Hearing Loss: Device Development and Validation","year":2023,"lang":"en","type":"article","venue":"JMIRx Med","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Boosting (machine learning); Modal; Audiology; Sensory system; Hearing loss; Computer science; Psychology; Medicine; Artificial intelligence; Cognitive psychology; Materials science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001091421,0.0001347216,0.0001277784,0.0001695905,0.0003816921,0.0001733892,0.0001106761,0.00005804871,0.00004752787],"category_scores_gemma":[0.001036848,0.0001360811,0.00002566823,0.0003712484,0.0000345853,0.0003490448,0.00009692864,0.0001755993,0.000640024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008847184,"about_ca_system_score_gemma":0.00005540883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007198938,"about_ca_topic_score_gemma":0.00002553852,"domain_scores_codex":[0.9986526,0.00005439683,0.0002691002,0.00044115,0.0002472482,0.0003355566],"domain_scores_gemma":[0.9991801,0.0003483003,0.00007423759,0.0001975476,0.00006295642,0.0001369059],"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":[0.00001806464,0.00001828545,0.00247037,0.00002749687,0.000004278715,0.00005322793,0.001744799,0.00008991375,0.9902049,0.0001988179,0.00009141306,0.005078456],"study_design_scores_gemma":[0.0002410509,0.00002994286,0.02438678,0.00003490701,0.000004632479,0.00003063455,0.0001813738,0.0002152012,0.9642372,0.00008206123,0.01036065,0.0001955746],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961088,0.000001705086,0.00008005227,0.001310827,0.0006509228,0.0002865017,0.00001154262,0.0002781076,0.001271544],"genre_scores_gemma":[0.989776,0.000004153339,0.0007276934,0.0005754271,0.0001225796,0.00006668979,0.000005958482,0.00002284359,0.008698659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02596769,"threshold_uncertainty_score":0.8226428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07621648500749494,"score_gpt":0.3473212138731239,"score_spread":0.2711047288656289,"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."}}