Can i [F W ]eed you some [F J ]ood? The role of subphonemic cues in word recognition
Bibliographic record
Abstract
A study that was conducted to examine the role of subphonemic cues in word recognition is presented. Researchers agree that coarticulation is the result of the vocal tract producing gestures in 'real time' by transitioning instantaneously from one target configuration to the next. When it comes to the degree, role and function of coarticulation, however, conflicting theories and findings abound. The goal of this study is to find out if and to what extent coarticulatory properties have an impact on spoken word recognition. A female adult speaker of Canadian English produced each word three times. One of the tokens was chosen to prepare the spliced stimulus items. The most important finding for our purposes is that of the phonological mapping negativity (PMN). The PMN, a negative-going component (N280) that peaks around the 200-300 ms range, is elicited by a phonological mismatch between the expected and heard onset of a target. The PMN has been understood to be sensitive to phonological processing.
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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 | 0.006 |
| 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 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".