Additivity of factor effects in reading tasks is still a challenge for computational models: Reply to Ziegler, Perry, and Zorzi (2009).
Bibliographic record
Abstract
J. C. Ziegler, C. Perry, and M. Zorzi (2009) have claimed that their connectionist dual process model (CDP+) can simulate the data reported by S. O'Malley and D. Besner. Most centrally, they have claimed that the model simulates additive effects of stimulus quality and word frequency on the time to read aloud when words and nonwords are randomly intermixed. This work represents an important attempt given that computational models of reading processes have to date largely ignored the issue of whether it is possible to simulate additive effects. Despite CDP+'s success at capturing many other phenomena, it is clear that CDP+ fails to capture the full pattern seen with skilled readers in these experiments.
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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 | 0.016 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.004 | 0.018 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.014 | 0.042 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".