Bibliographic record
Abstract
Lervag and Hulme's neuro-developmental theory and Wolf and Bowers's double-deficit hypothesis were examined in this longitudinal study. A total of 130 children were tested in preschool and followed through fifth grade, when 84 remained in the study. During preschool and kindergarten the participants were given tests of end-sound discrimination (phonological awareness; PA) and the rapid naming of objects (rapid automatic naming; RAN) and were placed into the four groupings of the double-deficit hypothesis. The growth curves for the four groups with the subtests of word reading, pseudoword reading, and comprehension supported the double-deficit hypothesis. The RAN objects scores of preschool and kindergarten predicted reading at every age level and offered support for Lervag and Hulme's neuro-developmental theory. It was concluded that both RAN and PA predicted reading in the English language throughout the elementary school years and that the early assessments of these variables were more diagnostic than measures at later ages.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".