Comparison of the egg flotation and egg candling techniques for estimating incubation day of Canada Goose nests
Bibliographic record
Abstract
ABSTRACT Both egg flotation and egg candling have been used to estimate incubation day (often termed nest age) in nesting birds, but little is known about the relative accuracy of these two techniques. We used both egg flotation and egg candling to estimate incubation day for Canada Geese (Branta canadensis interior) nesting near Cape Churchill, Manitoba, from 2000 to 2007. We modeled variation in the difference between estimates of incubation day using each technique as a function of true incubation day, as well as, variation in error rates with each technique as a function of the true incubation day. We also evaluated the effect of error in the estimated incubation day on estimates of daily survival rate (DSR) and nest success using simulations. The mean difference between concurrent estimates of incubation day based on egg flotation minus egg candling at the same nest was 0.85 ± 0.06 (SE) days. The positive difference in favor of egg flotation and the magnitude of the difference in estimates of incubation day did not vary as a function of true incubation day. Overall, both egg flotation and egg candling overestimated incubation day early in incubation and underestimated incubation day later in incubation. The average difference between true hatch date and estimated hatch date did not differ from zero ( days) for egg flotation, but egg candling overestimated true hatch date by about 1 d (true – estimated; days). Our simulations suggested that error associated with estimating the incubation day of nests and subsequently exposure days using either egg candling or egg flotation would have minimal effects on estimates of DSR and nest success. Although egg flotation was slightly less biased, both methods provided comparable and accurate estimates of incubation day and subsequent estimates of hatch date and nest success throughout the entire incubation period.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".