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Record W4409699294 · doi:10.22215/cujs.v3i2.5102

Investigating the Cross Stage Impacts of High Temperatures During Egg Development in Gryllodes sigillatus

2025· article· en· W4409699294 on OpenAlexaff
Hunter Brzezinski, Jacinta D. Kong, Heath MacMillian

Bibliographic record

VenueCarleton undergraduate journal of science. · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsCarleton University
Fundersnot available
KeywordsStage (stratigraphy)BiologyPaleontology

Abstract

fetched live from OpenAlex

Temperature significantly influences metabolism and growth in insects. Most insects are ectotherms, animals that do not produce useful body heat internally and whose body temperature closely matches their environmental temperature. While previous studies have primarily examined the impacts of short-term stressful changes in temperature or constant temperature exposure throughout all life stages, the extent to which early thermal history affects cross-stage development remains unclear. Addressing this knowledge gap, we distributed the eggs of a commercially-relevant cricket species raised as food and feed, Gryllodes sigillatus, across a thermal gradient ranging from 22°C to 40°C to assess relative hatching success and rate. It was indicated that higher temperatures (above the optimal 32°C) resulted in an increased hatching rate, while treatment groups with lower temperatures had a slower hatching rate or failed to do so. Further, decreased performance was observed for the highest temperature group (39°C), showing that the thermal limit was not achieved. A better understanding of these interactions with temperature will allow for more informed decisions for commercial rearing conditions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.281
Teacher spread0.271 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2025
Admission routes1
Has abstractyes

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