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Record W2886237193 · doi:10.1139/cjz-2017-0330

Evaluation of the combined temperature and relative humidity preferences of the Colombian terrestrial salamander <i>Bolitoglossa ramosi</i> (Amphibia: Plethodontidae)

2018· article· en· W2886237193 on OpenAlexvenueno aff
Carlos Galindo, Erika X. Cruz, Manuel Hernando Bernal

Bibliographic record

VenueCanadian Journal of Zoology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsnot available
FundersUniversidad del Tolima
KeywordsThermoregulationRelative humidityBiologyHydric soilTemperature gradientHumidityEcologyAtmospheric sciencesPhysicsMeteorologySoil water

Abstract

fetched live from OpenAlex

Temperature and humidity are critical factors for terrestrial lungless salamanders, as their body temperatures are largely determined by the environmental temperature and require moisture to sustain cutaneous respiration. Herein, we evaluated the preference of Bolitoglossa ramosi Brame and Wake, 1972 between a high temperature and a high relative humidity (RH), the influence of temperature on RH preferences, and the influence of RH on the thermal preferences. This study was performed in a field location in the municipality of Líbano, Tolima, Colombia. There, on different nights, we collected 84 adult B. ramosi and carried out the preference experiments, using aluminum troughs with different thermal and RH gradients. We found that between high temperature and high RH, B. ramosi preferred high RH. However, B. ramosi selected high temperatures when the gradient had a high RH and low temperatures when the gradient had a low RH. These results show that B. ramosi is able to thermoregulate and hydroregulate. Nevertheless, hydroregulation seems to be more important than thermoregulation because B. ramosi always selected the high RH gradients, while their thermal selection relied on the hydric environment.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

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 studies0.0000.000
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 head0.026
GPT teacher head0.247
Teacher spread0.221 · 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

Citations24
Published2018
Admission routes1
Has abstractyes

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