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
The birth prevalence of orofacial clefts, one of the most common congenital anomalies, is approximately one in 700 live births, but varies with geography, ethnicity, and socio-economic status. There is a variation in infant mortality and access to care both between and within countries, so some clefts remain unrepaired into adulthood. Quality of care also varies, and even among repaired clefts there is residual deformity and morbidity that significantly affects some children. The two major issues in attempts to address these inequalities are (a) etiology/possibilities for prevention and (b) management and quality of care. For prevention, collaborative research efforts are required in developing countries, in line with the WHO approach to implement the recommendations of the 2008 Millennium Development Goals (www.un.org/millenniumgoals). This includes the "common risk factor" approach, which analyzes biological and social determinants of health alongside other chronic health problems such as diabetes and obesity, as outlined in the Marmot Health inequalities review (2008) (www.ucl.ac.uk/gheg/marmotreview). Simultaneously, orofacial cleft research should involve clinical researchers to identify inequalities in access to treatment and identify the best interventions for minimizing mortality and residual deformity. The future research agenda also requires engagement with implementation science to get research findings into practice.
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 | 0.000 |
| 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) | 0.000 | 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