Bibliographic record
Abstract
In June and July, 2002, Jacques Whitford conducted a pilot study to investigate heart rate response in moulting Black Ducks (Anas rubripes) to jet aircraft activity within the military Low-level Training Area (LLTA) at Lac Fourmont, Labrador. From 15 male Black Ducks captured and released in the field, the study team was able to monitor 10 individuals fitted with heart rate monitors during a series of military aircraft events. Twenty-four aircraft noise events were recorded while monitoring six telemetered black ducks. Maximum estimated and modeled noise exposures to each telemetered duck being monitored ranged from 55-120+ dB. Based on a review of all data, including those instances when inadequate sample of heart rate vlues either before or following a noise event occurred, there were occasions when reactions were suggestive of a ‘startle effect’. An additional five noise events occurred when non-telemetered black duck were visible but no overt reaction or change in activity was detected. Black ducks were rarely observed after the water level at Lac Fourmont increased dramatically during 9-10 July. In a previous draft report outlining the results (August 2003), heart rate data was assessed as untransformed pulse periods using autocorrelation, spectral, and runs analyses. The outcome of the analyses was that the results were inconclusive given the available data. Following the receipt of two
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.478 | 0.358 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".