Additional file 1 of Sonometric assessment of cough predicts extubation failure: SonoWean—a proof-of-concept study
Bibliographic record
Abstract
Additional file 1. Supplemental Fig 1: Description of the Pulsar Model 14® Sound Level Meter and method for measurement. The Model 14 is a general purpose digital sound level meter which meets the full requirements of IEC 61672 to Class 2. Before each inclusion the Sound Level Meter was calibrated acoustically using an external reference, i.e the Sound Level Calibrator Model 106, which is placed over the microphone. The calibrator generates a stabilized Sound Pressure Level of 94dB (+- 0.3dB) at a frequency of 1 kHz. Using a Low range (Low = 35dB to 100dB), maximum sound level was measured pressing the MAX HOLD button for at least ½ second and was ultimately noticed. A level of sound in decibels (L) is defined as ten times the base-10 logarithm of the ratio between two power-related quantities I (i.e cough-volume related sound) and Io (i.e the human hearing threshold) as follows: L = 10 * Log 10 (I/ Io). Thus, an apparent mild increase from 73 to 76 dB in sound level results in multiplying acoustic energy by a factor two.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.714 | 0.081 |
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".