Evidence for mate‐encounter <scp>A</scp> llee effect in an invasive longhorn beetle ( <scp>C</scp> oleoptera: <scp>C</scp> erambycidae)
Bibliographic record
Abstract
1. Limited empirical support is available for mate‐encounter A llee effects in invasive insects due to the logistical challenges of studying demographic trends in low‐density populations. 2. Traps baited with pheromone and spruce volatiles were used to monitor the abundance of female Tetropium fuscum F . ( C oleoptera: C erambycidae) at multiple sites in N ova S cotia in 2011 and 2012. Each female was dissected to determine the presence or absence of sperm in its spermatheca (mated or virgin female, respectively). 3. Both male and total T. fuscum abundance declined with increasing distance to the focal point of T. fuscum 's invasion. Female mating probability declined with male abundance and with distance from the invasion focus, and mating probabilities were very low at the most peripheral sites. Difficulty in encountering mates may thus contribute to limiting the spread of T. fuscum . 4. The approach outlined here could be integrated into existing surveys of wood borers using traps baited with semiochemicals to improve our understanding of the role of the mate‐encounter A llee effect in invasion dynamics.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".