Bibliographic record
Abstract
Individuals with neurological conditions have particularly complex and diverse needs, and diagnosis often results in profound life changes which can affect an individual's relationships, career prospects and expectations for the future. The recently published National Service Framework (NSF) for Long-Term Conditions (Department of Health, 2005) states that good communication and the provision of appropriate information are essential features of a quality care service; however, information continues to be given a low priority in the NHS. This is evident from the survey conducted by the Neurological Alliance (2001). Less than a quarter of respondents were happy with the information they received about their conditions from the NHS and felt that voluntary organizations provided the best support. However, it must be recognized that individuals often do not absorb all of the information they are given at time of diagnosis and, therefore, the NHS should not be held solely responsible for the provision of health information. Patients should be given the opportunity to discuss their diagnosis at a time that is convenient to them and from a source that they choose, for example, a specialist health organization.
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 | 0.045 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.030 | 0.014 |
| Scholarly communication | 0.023 | 0.018 |
| Open science | 0.004 | 0.035 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.029 | 0.006 |
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".