Sampling Syrphidae using Malaise and Nzi traps on Akimiski Island, Nunavut.
Bibliographic record
Abstract
Flower flies (Diptera: Syrphidae) are a diverse group of pollinators found almost worldwide. Species surveys of these flies provide unique challenges as they can be difficult to collect due to different trapping biases. Here, we test the efficacy of the Nzi trap for use in the collection of syrphids by comparing the richness and abundance of syrphids caught in a Malaise trap and Nzi trap, July, 2012-2017 on Akimiski Island, Nunavut. We found that the Nzi trap caught many of the same species and in similar abundances as the Malaise trap, except for Platycheirus kelloggi (Snow), of which more were caught in the Nzi than the Malaise. The high capture rate of P. kelloggi using Nzi traps could be due to the flies’ unique shelter- or mate-seeking behaviours related to structure or colour. Using collections from 2008-2017, we also provide new territory records for 55 species and range extensions for 19 species. Two of these, Platycheirus kelloggi and Platycheirus latitarsis Vockeroth, had previously been reported only west of the Rocky Mountains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".