Use of time in a decision‐making process by a parasitoid
Bibliographic record
Abstract
1. Time perception is seldom studied in invertebrates, with the limited experimental evidence being insufficient to provide a comprehensive pattern of the capacity of invertebrates to measure time and use it in decision‐making processes. 2. In this study, it was hypothesized that insect parasitoids have evolved the capacity to measure time precisely and to use it to optimize foraging decisions related to host exploitation. To examine time perception in females of the gregarious egg parasitoid T richogramma euproctidis , the present study used their ability to adjust their investment (number of eggs laid) in a host to the initial transit duration (interval between the first contact with the host and the following contact with the substrate). Females utilize this method to assess host egg size, as a large egg necessarily requires more time to evaluate than a small host. In this study, the initial transit duration for a given sized egg was artificially extended by suspending it. 3. For similar sized hosts, female T . euproctidis significantly increased both oviposition duration and progeny allocation following a longer initial transit duration. 4. These results demonstrate the intrinsic capacity of this parasitoid to measure time and to adjust their progeny investment accordingly. This is believed to be one of the few demonstrations of a retrospective measure of time in an invertebrate.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".