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Record W2044720052 · doi:10.1002/arch.20365

Feeding through artificial membranes reduces fecundity for females of the blood‐feeding insect, <i>Rhodnius prolixus</i>

2010· article· en· W2044720052 on OpenAlexaff
R. Gary Chiang, Jennifer A. Chiang

Bibliographic record

VenueArchives of Insect Biochemistry and Physiology · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsRedeemer University
Fundersnot available
KeywordsRhodnius prolixusFecundityBiologyInsectBlood mealRhodniusReproductionZoologyHost (biology)EcologyAnimal sciencePopulation

Abstract

fetched live from OpenAlex

The blood-feeding insect, Rhodnius prolixus, has been raised in the laboratory for close to 100 years. Various feeding techniques have been employed ranging from the use of warm-blooded hosts, to the use of previously collected blood offered through artificial membranes. This study compared the fecundity in mated and unmated females fed rabbit blood directly from the shaved belly of a rabbit to that of females fed defibrinated rabbit blood through an artificial membrane. These results confirm previous reports that this insect's feeding efficacy is reduced using an artificial membrane. It also demonstrates for the first time that the fecundity index, which measures the efficiency of turning the blood meal into eggs, is significantly reduced. We suggest that the natural feeding on a warm-blooded host may provide cues that have the short-term effect of enhancing the act of feeding and the long-term effect of increasing egg production efficiency. Until an artificial feeding method that does not interfere with feeding and fecundity is devised, experiments on reproduction in R. prolixus warrant the use of a warm-blooded host to emulate feeding in its natural setting.

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)0.000
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 score0.064
Threshold uncertainty score0.301

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 studies0.0000.001
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 head0.044
GPT teacher head0.268
Teacher spread0.224 · 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

Citations8
Published2010
Admission routes1
Has abstractyes

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