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Record W4410906332 · doi:10.22621/cfn.v138i3.3147

Snow-surface activity of California Snow Scorpionfly, <i>Boreus californicus</i> (Mecoptera: Boreidae), in western Montana, USA

2025· article· en· W4410906332 on OpenAlexvenueno aff
Paul Hendricks

Bibliographic record

VenueThe Canadian Field-Naturalist · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFossil Insects in Amber
Canadian institutionsnot available
Fundersnot available
KeywordsSnowPhysical geographyEnvironmental scienceGeographyMeteorology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.014
GPT teacher head0.228
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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