Physiological measurements of human binaural processing
Bibliographic record
Abstract
Many different electric and magnetic responses to sound can be recorded as the human brain processes binaural information: (1) A binaural interaction component can be measured by comparing binaural responses to the sum of separate monaural responses. (2) Locating sounds in a reverberant environment can be examined by evaluating echo suppression. (3) Binaural beats can evoke following responses. (4) Responses can be evoked by binaural stimuli that are unmasked by changes in the interaural phase of stimulus or noise. (5) Occasional changes in the spatial location of a repeating sound can evoke a mismatch negativity. (6) A change in the binaural characteristics of an ongoing stimulus – interaural timing, correlation or phase – evokes a large N1-P2 response that is later than the response to the onset of a sound. The concomitant disruption and reinstatement of the 40-Hz steady state response can measure temporal perception and integration. (7) Moving sounds evoke large cortical responses when the movement begins and when a moving object crosses the midline. All paradigms may become useful in objectively demonstrating normal or abnormal binaural function in patients who cannot respond reliably during behavioral testing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".