Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study compared the lexical coverage provided by four wordlists [West’s (1953) General Service List (GSL), Nation’s (2006) most frequent 2,000 British National Corpus word families (BNC2000), Nation’s (2012) most frequent 2,000 British National Corpus and Corpus of Contemporary American-English word families (BNC/COCA2000), and Brezina and Gablasova’s (2015) New-GSL list] in 18 corpora. The comparison revealed that the headwords in the BNC/COCA2000 tended to provide the greatest average coverage. However, when the coverage of the most frequent 1,000, 1,500, and 1,996 headwords in the lists was compared, the New-GSL provided the highest coverage. The GSL had the worst performance using both criteria. Pedagogical and methodological implications related to second language (L2) vocabulary learning and teaching are discussed in detail.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.032 | 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 it