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Record W2588418841 · doi:10.1007/s13280-016-0879-1

Why geese benefit from the transition from natural vegetation to agriculture

2017· review· en· W2588418841 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

VenueAMBIO · 2017
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsAgricultureVegetation (pathology)Natural (archaeology)Transition (genetics)AgroforestryGeographyNatural resource economicsEnvironmental scienceEconomicsBiologyArchaeologyMedicine

Abstract

fetched live from OpenAlex

The energy and nutrient content of most agricultural crops are as good as or superior to natural foods for wild geese and they tend to be available in agricultural landscapes in far greater abundance. Artificial grasslands (fertilised native swards and intensively managed reseeds) offer far superior quality forage and higher intake rates than seminatural or natural grasslands. The availability of such abundant artificial food explains the abandonment of traditional habitats for farmland by geese over the last 50-100 years and favours no reduction in current levels of exploitation of agriculture. Continental scale spatial and temporal shifts among geese undergoing spring fattening confirm their flexibility to respond rapidly to broadscale changes in agriculture. These dramatic changes support the hypothesis that use of agricultural landscapes has contributed to elevated reproductive success and that European and North American farmland currently provides unrestricted winter carrying capacity for goose populations formerly limited by wetlands habitats prior to the agrarian revolution of the last century.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.092
GPT teacher head0.272
Teacher spread0.179 · 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

Quick stats

Citations157
Published2017
Admission routes1
Has abstractyes

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