Effect of Age on Lexical Decision Speed When Sentence Context Is Acoustically Distorted
Bibliographic record
Abstract
Many factors affect a listener's ability to understand spoken language, including the availability and supportiveness o f contextual information.In auditory lexical decision tasks, response times to target words are slowed when the preceding supportive context is acoustically distorted (Aydelott & Bates, 2004).In a previous study with normal-hearing younger adults, there was an effect o f the amount o f distortion, such that more acoustical distortion led to less facilitation by a congruent context (Pelletier, Goy, Coletta, Giroux, & Pichora-Fuller, 2010).Furthermore, distortion type affected lexical decision: when the sentence context was distorted by either time compression or lowpass filtering, congruent contexts facilitated lexical decision; however, incongruent contexts inhibited lexical decision only when the context was time-compressed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".