The Architecture of the Aquatic Environment and Its Influence on the Growth and Development of Tadpoles (Xenopus laevis)
Bibliographic record
Abstract
Many ecological factors are known to influence anuran growth and development. However, little is known about the influence of the shape of the aquatic environment. We investigated how the size of the air–water interface (surface area), water depth, and partitioning the aquatic space independently affect the growth and development of tadpoles of Xenopus laevis. To do this, we used a series of pyramidal frustra and partitioned aquaria. In our experimental containers, as the surface area decreased the dissolved oxygen concentration decreased and the tadpoles' air-breathing rates increased. As the depth of the water increased, the dissolved oxygen concentration decreased and the tadpoles' air-breathing rates increased. When the aquatic space was vertically partitioned to form a maze with corridors either 2 cm or 4 cm wide, the tadpoles avoided the narrow spaces between the partitions. Neither varying the surface area, nor vertically partitioning the aquatic space, significantly affected the growth or development of the tadpoles. However, the tadpoles raised in the shallower containers grew significantly slower than the tadpoles raised in the deeper containers. Tadpoles raised in shallow water behaved differently than those raised in deeper water. Shallow water appeared to prevent the tadpoles from ascending normally to break the surface tension of the water and properly air-breathe. Instead, the tadpoles in the shallow containers often floated at the surface, rather than in their normal position in the water column. Our study suggests that shallow water, independent of other variables such as water volume or dissolved oxygen concentration, may detrimentally impact air-breathing tadpoles, since shallow water appears to physically impede the animals' ability to air-breathe.
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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".