The effects of temperature and age on calling song in a field cricket with a complex calling song,<i>Teleogryllus oceanicus</i>(Orthoptera: Gryllidae)
Bibliographic record
Abstract
We examined the effects of temperature and age on calling song in the field cricket Teleogryllus oceanicus. Teleogryllus oceanicus has a complex calling song made up of two different kinds of chirp, long and short. The long chirp is made up of three to eight single pulses of sound and the short chirp consists of several paired pulses. The properties of T. oceanicus calling song did not vary with age, but almost every property of the song varied with temperature. Pulse duration, interpulse interval, and pulse rate in both the long and the short chirp varied with temperature. The number of pulses in the long chirp, number of chirps in the short chirp, chirp rate in the short chirp, duration of the long chirp, carrier frequency of both the short and long chirps, and total song duration were also affected by temperature. The duration of the short chirp and the degree of frequency modulation were the only characteristics that did not vary with temperature. Temperature does not affect the properties of the long and short chirps in the same manner. The long chirp decreases in duration with temperature and has fewer pulses, while the short chirp stays the same in duration and contains a higher number of chirps. These data demonstrate that temperature influences calling-song parameters in a field cricket with a complex calling song.
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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 | 0.000 | 0.000 |
| 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".