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
In Brief In this article, we argue in favor of quality assessment for qualitative studies and propose using a strategy we have labeled recognizability to assess external validity and facilitate knowledge transfer. To test our idea, we gathered data about recognizability in relation to a specific study on facial disfigurement. Four categories were identified: full recognition; partial recognition; recognition in others; and no recognition. In this article, we show how we used these categories both to evaluate the quality of our study and to assess its external validity. We also discuss the implications of recognizability for knowledge transfer. In this paper we propose using a strategy we have labelled recognizability to assess external validity and facilitate knowledge transfer. To test our idea, we gathered data about recognizability in relation to a specific study on facial disfigurement. Four categories were identified; Full recognition, Partial recognition, Recognition in others and No recognition. www.advancesinnursingscience.com
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it