Bibliographic record
Abstract
Nutrition support should be considered optional when this therapy is not in congruence with an individual's wishes based on quality of life goals, during the end-of-life period. Ethical dilemmas, dealing with nutrition therapy, are often due to lack of early communication between individuals, their family, and healthcare providers. Landmark young adult ethical court cases, dealing with nutrition therapy, reveal that this is not just a topic for the elderly. Healthcare literacy, multicultural populations, and different faiths add to the diversity of perspectives on healthcare decisions dealing with withholding or withdrawing nutrition therapy. These dilemmas are preventable if action steps are taken to improve the current healthcare clinical ethics model. Healthcare decision-making in advance should be considered by the individual and their family as an opportunity to communicate and plan for the future rather than a taboo topic. Healthcare facilities need to develop a proactive, integrated, structured process for healthcare ethical decision-making with measurable outcomes and shared best practice. Resources and toolkits are available to educate both the healthcare professional and the public on advance care planning
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.039 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.021 | 0.026 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".