Endoscopic scoring of mucus quantity and quality: observer and horse variance and relationship to inflammation, mucus viscoelasticity and volume
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
REASONS FOR PERFORMING STUDY: Endoscopic scoring of airway mucus quantity and quality has not been critically assessed. OBJECTIVES: To evaluate mucus scores for 1) observer- and horse-related variance and 2) association with inflammation, mucus viscoelasticity and measured volume. METHODS: Variance of scoring within and between observers and over time within horses were determined for airway mucus accumulation, apparent viscosity, localisation and colour, and correlations of mucus accumulation scores with neutrophil ratios in secretions. The relationship of accumulation score to measured volumes of 'artificial mucus' was investigated. Correlations of mucus accumulation, apparent viscosity and colour scores with measured viscoelasticity were tested. Viscoelasticity was compared between tracheal secretion samples collected ventrally and dorsally. RESULTS: Mucus accumulation scoring showed excellent interobserver agreement and moderate horse-related variance, was related to measured volumes of 'artificial mucus', and correlated well with neutrophilic airway inflammation. Scores of mucus viscosity, colour and localisation showed high observer-related variance. Mucus accumulation, apparent viscosity and colour scores did not correlate with measured tracheal mucus viscoelasticity, but dorsally-localised mucus showed 2-fold higher measured viscoelasticity than ventrally-localised samples. CONCLUSIONS: Mucus accumulation scores are a reproducible measure of mucus volumes in the trachea. POTENTIAL RELEVANCE: Endoscopic scoring of mucus accumulation is a reliable clinical and research tool. In contrast, apparent viscosity, localisation and colour scores should be interpreted with caution.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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