MétaCan
Menu
Back to cohort
Record W4406187388 · doi:10.1163/23524588-00001365

Diet particle size influences tropical house cricket life history

2025· article· en· W4406187388 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Insects as Food and Feed · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Utilization and Effects
Canadian institutionsCarleton University
Fundersnot available
KeywordsCricketParticle sizeBiologyAnimal scienceZoology

Abstract

fetched live from OpenAlex

Abstract Artificial diets are costly to produce, so diet efficiency is critically important to the success of mass rearing insects. One way to improve feed efficiency is through dietary particle size optimization. We tested whether individual crickets ( Gryllodes sigillatus ) reared on diets of different particle sizes (0.088-0.125 mm, 0.5-0.7 mm, and 1.0-1.4 mm) would grow differently. Crickets fed a diet ≥0.5 mm grew heavier during the first three weeks but weighed the same after six weeks regardless of diet size. We also tested for dietary size preference, and given a choice crickets consumed the most feed from the 1.0-1.4 mm diet. Next, we tested whether grinding diet to a powder and also pelleting the powder could influence life history. Powdered diet did not influence growth or development, but crickets fed a 2 mm pelleted diet grew larger body size. Overall, our results demonstrate that diet particle size can be leveraged to enhance cricket life history traits important to mass production, as growth was accelerated on larger particle size diets and crickets preferred to eat larger-sized diets. Researchers focusing on physical properties of insect diets should carefully consider the timing of growth and development milestones through which diet particle size may influence feed efficiency.

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.759
Threshold uncertainty score0.177

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.020
GPT teacher head0.227
Teacher spread0.207 · 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