Numerical and experimental validation of heat and mass transfer during heat treatment of wood
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
Public health ethics is the discipline that ensures that public health professionals and policy makers explain what they do, and why. During the COVID-19 pandemic, ethical deliberations often did not feature explicitly in public health decisions, thus reducing transparency and consistency in decision-making processes, and resulting in loss of trust by the general public. A public health ethics framework based on principles would add to transparency and consistency in public health decision-making. A framework of seven principles is presented and illustrated by applying them to vital COVID-19 ethical questions. Next the question of COVID-19 vaccination shows how the principles work in conjunction. In conclusion, embedding explicit ethical analysis in public health work is necessary to be trustworthy and regain trust. Preparedness for future challenges implies making the public health community more 'ethically literate'.
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 | 0.000 | 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