Factors influencing the assessment of lung function in mice with influenza-induced lung disease
Bibliographic record
Abstract
BACKGROUND: The constant-phase model (CPM) is commonly fit to respiratory system input impedance (Zrs) to estimate lung mechanics. Driving signal frequencies and the method of model fitting may influence the results, especially in cases of severe lung disease or under severe bronchoconstriction. OBJECTIVE: To illustrate the effects of different CPM fits to Zrs data using a mouse model of influenza-induced lung disease. METHODS: BALB/c mice infected with influenza (or control) were challenged with methacholine. The CPM was fitted to Zrs, measured between 0·25 and 19·625 Hz, using both unweighted and weighted fits. The effect of different lowest frequencies was assessed. RESULTS AND CONCLUSIONS: For influenza-infected mice, the unweighted fit was poor, and airway resistance (Raw) was often biologically impossible. The weighted fit provided more realistic estimates of Raw. Different model fits and minimal frequencies had little effect on tissue mechanics.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".