Bibliographic record
Abstract
Four invasive fish species, collectively known as Asian carps, have the potential to establish in the Great Lakes basin. To aid in prevention efforts, research was undertaken to understand factors influencing Asian carp spawning success. As Asian carp egg movement and hatching time are dependent on water temperature and hydrodynamics, this thesis focused on predicting in which rivers, and in which temperature and flow scenarios, successful hatching is more likely to occur. Chapter Two used existing temperature and velocity data to preliminary assess the spawning potential of eight Toronto-area tributaries. The results showed that Asian carp have substantial inter-annual variation in spawning potential and provided a method that had widespread applicability to narrow down potential spawning tributaries in the Great Lakes basin. Chapter Three created a novel coupling of three-dimensional (3-D) hydrodynamic river model and a 3-D Lagrangian Particle Tracker to model Grass Carp egg movement during a 2017 high-flow event in the Sandusky River, OH. The inclusion of 3-D aspects of flow allowed for the simulation of low-velocity dead zones that retain and re-suspend eggs, thereby increasing their residence time in rivers. The results showed that Grass Carp could spawn in shorter river lengths than previously predicted, thereby raising the potential of establishment in the Great Lakes basin. Chapter Four developed a coupled model on the Don River, ON to test the impact of potential barriers on spawning success. The results showed that in-river hatching rates could be greatly reduced by limiting upstream passage of carp and created a method that can be used to assess future potential barrier placements. Chapter Five added a novel temperature model coupling to the developed Sandusky River model to incorporate spatial and temporally varying temperature in the particle tracking. The results showed that the inclusion of varying temperature led to significant changes in in-river hatching rates. Climate-change scenarios model runs indicated that egg hatching times may reduce substantially due to anthropogenic climate change. The thesis results are directly applicable to prevention efforts in the Great Lakes and represent an advancement in the modelling of Asian carp spawning.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".