Snow-surface activity of California Snow Scorpionfly, <i>Boreus californicus</i> (Mecoptera: Boreidae), in western Montana, USA
Bibliographic record
Abstract
The flightless California Snow Scorpionfly (Boreus californicus Packard) has rarely been studied, and knowledge of its distribution and activity on snow remains fragmentary. I found it on snow surfaces in western Montana, USA, from valley grasslands to subalpine conifer forests and above the tree line. At lower elevations (991–1500 m), B. californicus was present on snow from early November to early March, at higher elevations (1800–2850 m), from early October to early January as well as late June. The species has now been documented in western Montana over an elevation gradient of nearly 2000 m and is probably active somewhere on snow in most months except in mid- and late summer. When the insect was present on snow, surface temperatures ranged from −5.0°C to 5.5°C. Pairs in copula (n = 26) were found when snow surface temperature was −0.5°C to 5.5°C. Mating occurred on snow at low elevations from November to late February, at high elevations in late June. The mating period in subalpine habitat, and probably above the tree line, includes early summer as well as late autumn to spring because of the colder temperatures and lingering snow in spring and earlier snowfall in autumn. Temperature and snow-cover characteristics affect the snow-surface ecology of B. californicus across its range in western Montana. Mating on a snow cover is likely related to greater mobility (ability to jump) on snow surfaces, aiding the search for mates and contributing to greater dispersal of eggs and reduced inbreeding.
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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) | 0.001 | 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".