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Record W2028320813 · doi:10.1673/031.011.6301

How Dietary Phosphorus Availability during Development Influences Condition and Life History Traits of the Cricket,<i>Acheta domesticas</i>

2011· article· en· W2028320813 on OpenAlexafffund
Laksanavadee Visanuvimol, Susan M. Bertram

Bibliographic record

VenueJournal of Insect Science · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Utilization and Effects
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAchetaBiologyPhosphorusCricketHerbivoreJuvenileEcologyOrthopteraGeneralist and specialist speciesLife history theoryAnimal scienceLife historyHabitat

Abstract

fetched live from OpenAlex

Phosphorus is extremely limited in the environment, often being 10-20 times lower in plants than what invertebrate herbivores require. This mismatch between resource availability and resource need can profoundly influence herbivore life history traits and fitness. This study investigated how dietary phosphorus availability influenced invertebrate growth, development time, consumption, condition, and lifespan using juvenile European house crickets, Acheta domesticus L. (Orthoptera: Gryllidae). Crickets reared on high phosphorus diets ate more food, gained more weight, were in better condition at maturity, and contained more phosphorus, nitrogen, and carbon in their bodies at death than crickets reared on low phosphorus diets. There was also a trend for crickets reared on high phosphorus diets to become larger adults (interaction with weight prior to the start of the experiment). These findings can be added to the small but growing number of studies that reveal the importance of phosphorus to insect life history traits. Future research should explore the importance of dietary phosphorus availability relative to protein, lipid, and carbohydrate availability.

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 score0.004
Threshold uncertainty score0.008

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 head0.054
GPT teacher head0.214
Teacher spread0.159 · 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

Citations42
Published2011
Admission routes2
Has abstractyes

Explore more

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