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Record W2132379362 · doi:10.1002/jez.10082

Energy and water conservation in frozen vs. supercooled larvae of the goldenrod gall fly, <i>Eurosta solidaginis</i> (fitch) (Diptera: Tephritidae)

2002· article· en· W2132379362 on OpenAlexaff
Jason T. Irwin, Richard Lee

Bibliographic record

VenueJournal of Experimental Zoology · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsMcGill University
Fundersnot available
KeywordsSupercoolingTephritidaeGallBiologyAnimal scienceBotanyMeteorology

Abstract

fetched live from OpenAlex

Insects that tolerate severe cold during winter may either supercool or tolerate ice forming within the tissues of the body. To compare the relative advantages of freezing and supercooling, we measured rates of CO(2) production and water loss in frozen and supercooled goldenrod gall fly larvae (Eurosta solidaginis). As an important first step, we measured the time required for ice content and metabolic rate to stabilize upon freezing. Ice content stabilized after only three hours of freezing at -5 degrees C, whereas CO(2) production required 12 hours to stabilize. Subsequent experiments found that freezing greatly reduced both water loss and metabolic rate. Comparisons of supercooled and frozen larvae at -5 degrees C indicated that CO(2) production fell 47% with freezing and water loss decreased 35%. As temperature decreased to -10 and -15 degrees C, CO(2) production fell exponentially and was no longer detectable at -20 degrees C with our measurement system. Our results demonstrate that freezing significantly reduces energy consumption during the winter and may therefore improve winter survival and spring fecundity. The advantages of freezing over supercooling would drive selection toward insect freeze tolerance and also toward higher supercooling points to increase the duration of freezing each winter.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

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)0.0000.000

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 head0.013
GPT teacher head0.206
Teacher spread0.193 · 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 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

Citations60
Published2002
Admission routes1
Has abstractyes

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