Timing of Hexagenia (Ephemeridae: Ephemeroptera) mayfly swarms
Bibliographic record
Abstract
Although degree-days can be used to determine when insect emergence begins, peak swarming events in species that exhibit extended emergence periods are difficult to estimate. With the aid of logistic regression, we estimated the probability of adult mayfly swarms (≥50 individuals/m2), occurring on any given night in western Lake Erie, using meteorological data. We sampled adult Hexagenia Walsh, 1863 from 2130 (sunset) to 2300 on 18 dates in 2000 (2 June – 18 July), with the largest numbers retrieved between 13 June and 2 July. Water temperature (20 °C) was the cue to the onset of swarming (subimagos). Highest mean (±SE) density of all Hexagenia adults (subimagos and imagos) was 24 740 ± 8 757 individuals/m2. Overall, 10-fold more imagos (mostly females) than subimagos were attracted to lights. Of the factors examined (air and water temperature, Julian day, dew point, heat index, humidity, moon phase, wind chill, wind direction, wind speed), onshore wind speed (0–9.2 km/h) on calendar dates for which the water temperature exceeded 20 °C was the most significant factor to account for total adult swarms. Eighty-three percent of the 18 swarming events observed in 2000 were correctly predicted. Validity of the model was confirmed with data collected in 2002, during which 5 of 6 swarming events were correctly predicted from the logistic model. Wind promotes adult aggregation at the land–water interface, the effect of which facilitates mating success and predator swamping.
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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 | 0.000 | 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) | 0.001 | 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".