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Record W2609909675 · doi:10.1139/cjas2013-036

Review: Genetics of helminth resistance in sheep

2014· article· en· W2609909675 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

VenueBioOne Complete (BioOne) · 2014
Typearticle
Languageen
FieldVeterinary
TopicHelminth infection and control
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHelminthsBiologyHelminth infectionsResistance (ecology)AlleleSelection (genetic algorithm)GeneticsZoologyGeneEcology

Abstract

fetched live from OpenAlex

Karrow, N. A., Goliboski, K., Stonos, N., Schenkel, F. and Peregrine, A. 2014. Review: Genetics of helminth resistance in sheep. Can. J. Anim. Sci. 94: 1-9. Gastrointestinal helminth parasites are an important source of economic loss to sheep producers. A rapid increase in anthelmintic resistance has occurred around the globe; therefore, the industry is exploring alternative strategies such as genetic selection to control losses attributed to helminth infection. Since helminths have co-evolved with sheep for millions of years, natural selection for enhanced helminth resistance has occurred within certain breeds from various parts of the world. These breeds of sheep are being used to better understand the genetic aspects of helminth resistance. If the genetic variants that contribute to this phenotype can be identified, it may be possible to use selection strategies to introduce resistance alleles into other breeds or to increase their frequency within breeds. This review will provide an up-to-date overview of the pathology of helminth disease, the immune response to helminth infection, and the search for genes that confer helminth resistance.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.001

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 head0.348
GPT teacher head0.302
Teacher spread0.046 · 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