Bibliographic record
Abstract
The Newest Vital Sign (NVS) is one of the most widely used health literacy screening instruments (Shealy & Threatt, 2016; Weiss et al., 2005). The original version of the NVS was developed in English and Spanish and validated in the United States for identifying people with limited health literacy skills (Weiss et al., 2005). Since then, the NVS has been adapted and validated for use in other languages and countries, including the United Kingdom (Rowlands et al., 2013), the Netherlands (Fransen et al., 2014), Japan (Kogure et al., 2014), Italy (Capecchi, Guazzini, Lorini, Santomauro, & Bonaccorsi, 2015), Kuwait (Al-Abdulrazzaqa, Al-Haddadb, AbdulRasoula, Al-Basarib, & Al-Taiara, 2015), Brazil (Rodrigues, de Andrade, González, Birolim & Mesas, 2017), China (Xue et al., 2018), and Canada (Mansfield, Wahba, Gillis, & Weiss, 2018). It has also been adapted for administration in American Sign Language (McKee et al., 2015).
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.
How this classification was reachedexpand
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 | 0.020 | 0.076 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".