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Record W3033487858 · doi:10.17161/jnah.vi.13613

MORPHOLOGY, REPRODUCTION, SEASONAL ACTIVITY AND HABITAT USE OF A NORTHERN POPULATION OF THE SMOOTH GREENSNAKE (OPHEODRYS VERNALIS)

2020· article· en· W3033487858 on OpenAlexaboutno aff
Pamela L. Rutherford, Nicholas A. Cairns

Bibliographic record

VenueThe Journal of North American Herpetology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyReproductionEcologyHabitatOviparityPopulationMatingMorphology (biology)ZoologyDemography

Abstract

fetched live from OpenAlex

The Smooth Greensnake (Opheodrys vernalis) is a small, slender, oviparous, colubrid snake that is widely distributed in North America. Nonetheless, there have been few studies on this species, and little is known about Canadian populations. The objective of this study was to examine morphology, reproduction, seasonal activity and habitat use of a northern population of the Smooth Greensnake. Individuals were captured during the summers of 2007-2010 in southwestern Manitoba, Canada. Females were larger and relatively heavier than males, but clutch size did not consistently increase with body size. In addition, 59% (on average) of available adult females were gravid in any given year, suggesting that females may not reproduce each year. Males had relatively longer heads and longer tails than females. Males were more common in early August; otherwise, females were more common. The peak of male activity in August suggests that fall mating might occur in this species, but this was not confirmed. Finally, Smooth Greensnakes were most commonly found in grassland, and there were no differences in habitat use between the sexes. Further research on northern populations of Smooth Greensnakes would provide valuable information on this little-studied species.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.304

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.223
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2020
Admission routes1
Has abstractyes

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