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Record W4399013785 · doi:10.1101/2024.05.23.595553

Applying nutritional ecology to optimize diets of crickets raised for food and feed

2024· preprint· en· W4399013785 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

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Utilization and Effects
Canadian institutionsCarleton University
Fundersnot available
KeywordsEcologyBiology

Abstract

fetched live from OpenAlex

Abstract Increasing yield is a primary goal of mass insect rearing for food and feed, and diet shapes insect life history traits important to yield, such as survival, development time, and body size at adulthood. Little is known about how developmental macronutrient intake impacts survival, growth, and adult body size of mass reared insects. Here, we applied the nutritional geometry framework and reared individual tropical house crickets ( Gryllodes sigillatus ) from hatch to adulthood on a wide range of protein:carbohydrate diets. We measured weekly food consumption, survival, development time to adulthood, and adult body size and mass, and calculated a yield metric to extrapolate our individual-level results and predict how diet influences yield at the mass rearing level. Yield was maximized on a 3 P :1 C diet, as crickets fed this diet were most likely to develop into adults and grew maximum mass and body size. When provided with a choice between diets, crickets selected a relatively balanced 1.05 P :1 C diet throughout development, but males consumed 17% more protein than females. Our results represent a crucial first step towards determining the optimal standard feed formulation required to maximize cricket farming yield.

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)0.000
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 score0.422
Threshold uncertainty score0.659

Codex and Gemma teacher scores by category

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 head0.021
GPT teacher head0.222
Teacher spread0.201 · 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