A swimming activity assay shows that the thermal tolerance of<i>Daphnia magna</i>is influenced by temperature acclimation
Bibliographic record
Abstract
Daphnia magna Straus, 1820 is a widespread zooplanktic organism enduring considerable changes in oxygen concentration and temperature within its natural habitat. The thermal tolerance window of D. magna was analyzed using the animals' swimming activity as a test parameter in a photometrical assay. Acclimation to different temperatures (10, 20, 30 °C) resulted in a shift of the thermal optimum corresponding to acclimation conditions. Acclimation to warm temperatures also increased the upper thermal tolerance limit in acute thermal tolerance tests. However, the magnitude of the resulting shift in the acute thermal tolerance (LT50) was much smaller. An increase in acclimation temperature by 10 °C changed the thermal optimum by approximately this value, whereas the LT50was enhanced only by 1–2 °C. The time course of the acclimation process was followed by surveying temperature-dependent swimming activity upon the transfer of animals raised in a medium at 20 °C to a medium at 30 °C. Maximum swimming intensity at 20 °C was lost within 3 days. The swimming behavior resembled that of animals acclimated to 30 °C after 2 weeks, indicating that acclimation to the elevated temperature was achieved.
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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) | 0.001 | 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".