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Record W1994067650 · doi:10.1603/0022-2585-40.1.22

Novel Growth Media for Rearing Larval Horn Flies,<i>Haematobia irritans</i>(Diptera: Muscidae)

2003· article· en· W1994067650 on OpenAlexaff
M. Alejandra Perotti, Tim Lysyk

Bibliographic record

VenueJournal of Medical Entomology · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForensic Entomology and Diptera Studies
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyMuscidaeLarvaHaematobia irritansMicrobiologyAgarAgar plateYolkAnimal scienceBotanyFood scienceBacteria

Abstract

fetched live from OpenAlex

Experiments were conducted to develop an agar-based medium for rearing immature horn flies, Hematobia irritans (L.). Larval survival was determined on sterilized manure inoculated with pure and mixed cultures of Acinetobacter sp., Bacillus pumilus Meyer & Gottheil, Comamonas acidovorans den Dooren de Jong, Pseudomonas mendocina Palleroni, Flavobacterium sp. and Empedobacter breve (Holmes & Owen). Rearing larvae on mixed cultures enhanced pupal weight but not survival. Horn fly larvae failed to survive when reared on standard bacteriological media inoculated with pure and mixed cultures of Acinetobacter sp., P. mendocina, and C. acidovorans. Larvae completed development on a minimal medium supplemented with alfalfa, egg proteins, and vitamins. Medium with low alfalfa content (30 g alfalfa/500 ml minimal medium) had enhanced survival when supplemented with egg yolk protein and vitamins. Medium with high alfalfa content (130 g alfalfa/500 ml minimal medium) had enhanced survival when supplemented with whole egg protein and vitamins. Survival was also favored when media were inoculated with pure cultures of Acinetobacter or Acinetobacter mixed with either Pseudomonas or Comamonas. Individual plates could support larvae developing from up to 40 eggs, and survival was least variable when plates were inoculated with greater numbers of eggs. This rearing system shows promise as a means for conducting standardized bioassays on a meridic diet.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.026
GPT teacher head0.255
Teacher spread0.229 · 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 designTheoretical or conceptual
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

Citations19
Published2003
Admission routes1
Has abstractyes

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