Predicting the distribution of the Chinese mystery snail, Cipangopaludina chinensis, a potentially invasive, non-indigenous species, in Atlantic Canada
Bibliographic record
Abstract
The Chinese mystery snail, Cipangopaludina chinensis, a freshwater mollusc indigenous to Eastern Asia, introduced to North America and Europe.Currently, little is known about C. chinensis in North America.My thesis objectives were to: (1) synthesize relevant literature and confirm whether C. chinensis should be considered invasive in North America, (2) determine the known species occurrence in continental North America highlighting reporting gaps, and (3) create a species distribution model for C. chinensis in the Maritimes.The literature review indicated that C. chinensis should be considered invasive in North America.The largest number of reported occurrences were in southern Ontario and northern US along the Great Lakes with the lowest in the Maritimes, the Prairies, Quebec, and near Lake Superior.Finally, a random forest model was developed to predict C. chinensis distribution in Nova Scotia, with highest probable occurrence in the Halifax-area, the New Brunswick-Nova Scotia border, and Cape Breton.it, supported me through every decision, and understood that I had my own path to follow.I will always appreciate the many life lessons you have taught me.Thank-you to my supervisory
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".