Inspiration: two decoupled diaphragms
Bibliographic record
Abstract
INTRODUCTION Although inspiratory airflow is generated primarily by the diaphragm, costal (COS) and crural (CRU) diaphragm have distinct neural-mechanical profiles and varying mechanical advantage. QUESTION Do COS and CRU make equivalent contributions to generation of inspiratory airflow? METHODS Data N=12 canines, from database completed in 2009, implanted with sonomicrometers and EMG electrodes into left COS and CRU. After recovery, while awake, airflow, muscle length and moving average EMG were recorded during room air and CO2 stimulation, analyzed breath by breath and expressed as percent of maximum at successive 5% "slices" of TTOT(%TTOT). RESULTS At room air, mechanical contributions of COS and CRU were significantly different (p<0.05), with COS progressively diverging to greater contribution than CRU (Figure 1). Peak EMG of COS and CRU did not occur at peak inspiratory airflow, but much later in inspiration. And the segments were asynchronous, with peak CRU EMG occurring consistently after COS (p<0.05) (Figure 2). CONCLUSIONS COS and CRU contributions to inspiratory airflow are significantly different, EMG activation is not in phase with inspiratory airflow, and segmental activity is asynchronous. erj;64/suppl_68/PA1664/F1 F1 F1 erj;64/suppl_68/PA1664/F2 F2 F2
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".