Lower chronic temperature limits in three common tropical aquarium fish
Bibliographic record
Abstract
Assessing the ability of tropical fish to survive winter temperatures typical of Canadian waterbodies is an important component of environmental risk assessments conducted for genetically engineered tropical aquarium fish introduced to Canada. We determined the lower temperature tolerance limits of three species: Betta splendens Regan, 1910, Pristella maxillaris (Ulrey, 1894), and Corydoras aeneus (Gill, 1858) currently available in genetically engineered strains, using modified chronic lethal minimum temperature trials. When temperature was lowered daily by 1 °C from a starting temperature of 20.5 °C, all species lost equilibrium at several degrees warmer than typical winter water temperatures in Canada (10.0 ± 1.2 °C Bettas, 12.7 ± 1.1 °C Corydoras, and 13.2 ± 0.5 °C Pristellas, typical winter water temperatures are 4 °C or less). Consequently any introduced individuals in the three species are not expected to overwinter, and hence do not have the ability to establish, in Canadian freshwater systems. Activity and feeding level decreased at 17.5–16.5 °C (Bettas), 16.5–15.5 °C (Pristellas), and 14.5–13.5 °C (Corydoras). As temperatures are expected to be below this in all but the summer months in most systems, introduced individuals would be expected to be limited spatially and temporally where they would be active enough to interact competitively or aggressively (Bettas only) with native species sharing similar niches.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".