Dilution of Fluon Before Trap Surface Treatment Has No Effect on Longhorned Beetle (Coleoptera: Cerambycidae) Captures
Bibliographic record
Abstract
Several studies have observed that trap captures of longhorned beetles (Coleoptera: Cerambycidae) can be increased by treating the surface of intercept traps with a lubricant. In addition to being expensive, these treatments can alter the spectral properties of intercept traps when applied neat. These surface treatments, particularly Fluon, are commonly used diluted as a low friction coating to prevent insects from climbing out of rearing containers. The purpose of this study was to examine the effect of diluting Fluon on the spectral properties of treated corrugated plastic traps and the capture of longhorned beetles including Monochamus scutellatus (Say), Monochamus mutator (LeConte), and Monochamus notatus (Drury). Intercept panel traps were baited with attractant semiochemicals and treated with either undiluted (i.e., 100%) Fluon, a 1:1 mixture of Fluon and water (50%), a 1:9 mixture of Fluon and water (10%), or untreated. There were no obvious differences in the relative reflectance of untreated black Coroplast plastic or black Coroplast plastic treated with 50 or 10% Fluon. Traps treated with 100% Fluon had similar patterns of peak reflectance to the other treatments but overall had higher relative reflectance. In general, no effect of diluting the Fluon was observed for male or female M. scutellatus or M. mutator , but an effect of treating traps with Fluon was observed. Similar results were observed for the combined captures of Clytus ruricola Olivier, Cyrtophorus verrucosus Olivier, Megacyllene caryae (Gahan), Xylotrechus colonus (F.), Neoclytus acuminatus (F.), Neoclytus mucronatus (F.), and Phymatodes testaceus (L.). No treatment effect was observed for M. notatus .
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".