Word recognition in individuals with left and right hemisphere damage: The role of lexical stress
Bibliographic record
Abstract
Lexical stress patterns appear to be important in word recognition processes in normal individuals. The present investigation employed a lexical decision task to assess whether left (LHD) and right hemisphere damaged (RHD) patients are similarly sensitive to stress patterns in lexical access. The results confirmed that individuals without brain damage are influenced by stress patterns, as indicated by increased lexical decision latencies to incorrectly stressed word and nonword stimuli. The data for the LHD patients revealed an effect of stress for real word targets only, whereas the reaction time data for the RHD patients as a group showed no significant influence of stress pattern. However, there was a great deal of individual variability in performance. The latency and error rate findings suggest that LHD patients and non-brain-damaged individuals are both sensitive to lexical stress in word recognition, but the LHD patients are more likely to treat incorrectly stressed items as nonwords. The results are discussed in relation to theories of the hemispheric lateralization of prosodic processing and the role of lexical stress in word recognition.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".