Simple and inexpensive devices to measure heart rates of incubating birds
Bibliographic record
Abstract
ABSTRACT Heart rate is a useful physiological index for studies of stress, locomotion, and activity patterns. Measuring heart rates of birds without the need to handle individuals is desirable when trapping is problematic or may cause unwanted disturbance. Heart-rate recorders housed in dummy eggs offer an effective solution, but the usefulness of previously described devices is limited by their size, complex construction, and reliance on analog media. We constructed egg-based, heart-rate monitors through simple modifications of inexpensive, commercially available MP3 players and Bluetooth headsets. We compared the merits of each device during tests in the laboratory, an aviary, and the field in 2008. Field testing was undertaken at Presqu’ile Provincial Park, Ontario, Canada, where we recorded heart rates of Common Terns (Sterna hirundo), Caspian Terns (Hydroprogne caspia), and Ring-billed Gulls (Larus delawarensis). Birds incubated dummy eggs normally, with no differences in behavior (all P > 0.05) when incubating either wired (MP3 players) or wireless (Bluetooth) devices. MP3 devices were more reliable in the field. Bluetooth devices often lost pairing with laptop computers (33% of files analyzed contained no signal), produced files with more obscuring noise, and only two could be deployed simultaneously with a single computer; there was no limit on how many MP3 devices could be deployed simultaneously. Common Terns, the smallest of our three focal species, had significantly higher (P < 0.001) mean heart rates (268.6 ± 9.3 beats per min [bpm]) than either Ring-billed Gulls (198.0 ± 7.1 bpm) or Caspian Terns (204.2 ± 8.0 bpm). Heart rates of all three species were consistent with those reported or predicted from previous studies. The MP3 devices we describe provide investigators with a simple, inexpensive, and minimally invasive way to digitally record heart rates of birds of almost any size.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".