Position paper on olfactory dysfunction
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- Meta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Not applicableConsensus signal: none
- Genre
- Candidate signal: ReviewConsensus signal: Review
- Teacher disagreement score
- 0.988
- Threshold uncertainty score
- 1.000
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.109 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
BACKGROUND: Olfactory dysfunction is an increasingly recognised condition, associated with reduced quality of life and major health outcomes such as neurodegeneration and death. However, translational research in this field is limited by heterogeneity in methodological approach, including definitions of impairment, improvement and appropriate assessment techniques. Accordingly, effective treatments for smell loss are limited. In an effort to encourage high quality and comparable work in this field, among others, we propose the following ideas and recommendations. Whilst the full set of recommendations are outlined in the main document, points include the following: - Patients with suspected olfactory loss should undergo a full examination of the head and neck, including rigid nasal endoscopy with small diameter endoscopes. - Subjective olfactory assessment should not be undertaken in isolation, given its poor reliability. - Psychophysical assessment tools used in clinical and research settings should include reliable and validated tests of odour threshold, and/or one of odour identification or discrimination. - Comprehensive chemosensory assessment should include gustatory screening. - Smell training can be helpful in patients with olfactory loss of several aetiologies. CONCLUSIONS: We hope the current manuscript will encourage clinicians and researchers to adopt a common language, and in so doing, increase the methodological quality, consistency and generalisability of work in this field.
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.
The record
- Venue
- Rhinology Journal
- Topic
- Olfactory and Sensory Function Studies
- Field
- Neuroscience
- Canadian institutions
- Université du Québec à Trois-RivièresHôpital du Sacré-Cœur de Montréal
- Funders
- not available
- Keywords
- MedicineHyposmiaPosition paperIdentification (biology)Intensive care medicineConsistency (knowledge bases)PathologyDiseaseArtificial intelligenceComputer science
- Has abstract in OpenAlex
- yes