Bibliographic record
Abstract
Abstract We follow up on our research demonstrating that aero-tactile information can enhance or interfere with accurate au-ditory perception, even among uninformed and untrained per-ceivers [1]. Mimicking aspiration, we applied slight, inaudibleair puffs on participants’ skin at the ankle, simultaneously withsyllables beginning with aspirated (‘pa’, ‘ta’) and unaspirated(‘ba’, ‘da’) stops, dividing the participants into two groups,thosewithhairy,andthosewithhairlessankles. Sincehairfolli-cleendings(mechanoreceptors)areusedtodetectairturbulence[2] we expected, and observed, that syllables heard simultane-ously with cutaneous air puffs would be more likely to be heardas aspirated, but only among those with hairy ankles. Theseresults demonstrate that information from any part of the bodycan be integrated in speech perception, but the stimuli must beunambiguously relatable to the speech event in order to be inte-grated into speech perception.Index Terms: speech perception, aero-tactile integration, em-bodiment theory
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
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".