MétaCan
Menu
Back to cohort
Record W2013894804 · doi:10.1073/pnas.1018904108

Population trends of grassland birds in North America are linked to the prevalence of an agricultural epizootic in Europe

2011· article· en· W2013894804 on OpenAlexafffund
Joseph J. Nocera, Hannah M. Koslowsky

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsTrent UniversityMinistry of Natural Resources and Forestry
FundersMinistry of Natural Resources
KeywordsOutbreakEpizooticBovine spongiform encephalopathyGeographyLivestockHayGrasslandPopulationAgricultureSocioeconomicsEcologyBiologyDiseaseForestryEnvironmental healthMedicineAgronomyEconomics

Abstract

fetched live from OpenAlex

Globalization of trade has dramatic socioeconomic effects, and, intuitively, significant ecological effects should follow. However, few quantitative examples exist of the interrelationship of globalization, socioeconomics, and ecological patterns. We present a striking illustration of a cascade in which bovine spongiform encephalopathy (BSE; "mad cow disease") outbreaks in Europe exerted pressure on global beef markets, subsequently affecting North American hayfields and grassland bird populations. We examined competing models, which linked the prevalence of BSE in five focal countries, volume of beef exports to those countries from North America, and the amount of hayfield harvested and the abundance of grassland birds in North America. We found that (i) imports from North America increased 1 y after BSE outbreaks; (ii) probably because fewer cattle remained, the hay harvest in North America was reduced 2 y after the outbreak; (iii) the reduced hay harvest yielded a positive response in grassland bird populations 3 y after the outbreak.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.074
GPT teacher head0.280
Teacher spread0.206 · 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 designObservational
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

Citations14
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicAnimal Disease Management and EpidemiologyFrench-language works237,207