Bibliographic record
Abstract
Under collaborative flight research project with NASA and, separately, Air Canada, the NRC has investigated meteorological infrasound sensing, using NASA-developed Infrasound sensing microphones. The project involved the installation of 1.5-inch NASA microphone in the nosebay of the NRC DHC-6 research aeroplane. The microphone was plumbed to a pitot-static tube line, connected to a research pitot-static tube on the starboard side of the aircraft nose. Microphone signals on the DHC-6 installation were validated during orbiting flight through its own wake vortices, and flight in the vicinity of wake vortices from Medium Category jets landing at Ottawa Airport. Thereafter, flights were undertaken, to measure the infrasound sensing of meteorological features. Possible acoustic ducting of infrasound energy was measured in stratified lower atmospheric conditions. Infrasound sensing was also accomplished, in the vicinity of meteorological flow-fields of relatively concentrated vorticity, notably line features of vorticity. An increase in sensed infrasound energy was recorded as distance to the line features reduced. Convective uplift infrasound signature sensing was also conducted, and indicated a similar result.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".