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Review of host pulmonary defenses with reference to cattle

2013· article· en· W3000220265 on OpenAlexaff
Heidi E. Banse, Amelia Wollums, D. L. Step

Bibliographic record

VenueThe Bovine Practitioner · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsImmune systemImmunologyRespiratory tractPathogenBiologyInnate immune systemBovine respiratory diseasePhagocytosisDiseaseAcquired immune systemOpsoninRespiratory diseaseSecretionRespiratory tract infectionsRespiratory systemLungMedicine

Abstract

fetched live from OpenAlex

Bovine respiratory disease is a leading cause of morbidity and mortality for the cattle industry. Cattle can be protected from respiratory disease by both structural and dynamic defense mechanisms of the respiratory tract, which are critical for prevention of pathogen entry and colonization. Dynamic defenses include those mediated by the innate and adaptive branches of the immune response. The immune response to pathogens is complex, and requires immune cell migration, proliferation, and adaptation. Secretion of molecules, including cytokines, host defense peptides, and opsonins, by cells within the respiratory tract promotes respiratory defense, including pathogen neutralization and phagocytosis. Ongoing discoveries in the field of immunology should guide the development of novel immunotherapeutic interventions for the prevention and treatment of bovine respiratory disease.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.003

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 head0.024
GPT teacher head0.287
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2013
Admission routes1
Has abstractyes

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