Modeling round goby Neogobius melanostomus range expansion in a Canadian river system
Bibliographic record
Abstract
Abstract We applied a gamma transit time model to predict the rate of range expansion of the round goby ( Neogobius melanostomus Pallas, 1814) in the Trent-Severn Waterway (Ontario, Canada). Gamma distributions were fit to actual transit times of the population front from 2009 to 2011. A lack of model fit in the second year is thought to be indicative of an upstream bait bucket introduction, and this model may be useful for identifying such events. Range expansion predictions were highest in high quality habitats at 9.3 km/year, with a 5% probability that highly mobile individuals may disperse 27 km/year. The model also predicts the arrival time of the population at any distance from the population front with a given confidence interval. The estimation of a timeline for range expansion and determining underlying factors affecting the spread of invasive species could inform preventative strategies. This model is potentially useful in predicting transit times of other invasive species expanding their range in linear space, and in separating natural population expansion from additional human-assisted movement in the same system.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".