Bioenergetics and habitat suitability models for the Chinese mystery snail (<i>Bellamya chinensis</i>)
Bibliographic record
Abstract
Relatively little is known about the invasive Chinese mystery snail (Bellamya chinensis). This research aims to elucidate some of the mystery surrounding this species. First, we place the species in context with other invasive freshwater snails of the USA and Canada, identifying current information gaps, categorizing shared characteristics among families and species, and comparing functional roles and ecological effects of freshwater snails. We conclude that more focus needs to be directed to regulating the aquarium, pet, and food trades if we are serious about preventing future invasions. Next, we develop a bioenergetics model for the species by quantifying and comparing consumption, egestion, respiration, and production of the Chinese mystery snail at varying water temperatures. We observed differences in these values across different water temperatures, indicating that temperature affects growth and reproductive strategies of this species. Then we focused on analyzing a specific case study to identify physical, chemical, and biological lake characteristics that help predict where the Chinese mystery snail is found. The top predictor model found that Chinese mystery snail presence is correlated with Secchi depth, latitude, and the presence of other aquatic invasive species. Finally, we use network analysis to develop a method for coupling social and ecological network models so they may be used in tandem to assess how humans aid the movement of the Chinese mystery snail, as well as how the snail affects an ecosystem after invasion. This was achieved through the adaptation of the framework of infectious disease network modeling. Advisors: Kevin L. Pope and Valery E. Forbes
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".