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Record W2808553025 · doi:10.1126/sciadv.aas9383

Anthropogenic changes to the Holocene nitrogen cycle in Ireland

2018· article· en· W2808553025 on OpenAlexaff
Eric Guiry, Fiona Beglane, Paul Szpak, Rick Schulting, Finbar McCormick, Michael P. Richards

Bibliographic record

VenueScience Advances · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsSimon Fraser UniversityTrent UniversityUniversity of British Columbia
FundersUniversity College CorkUniversity of GalwayNational University of IrelandIreland Canada University FoundationWenner-Gren Foundation
KeywordsHolocenePrehistoryBronze AgeNitrogenNitrogen cycleNorthern irelandBronzeArchaeologyPhysical geographyGeologyEnvironmental scienceGeographyChemistryHistoryEthnology

Abstract

fetched live from OpenAlex

Humans have always affected their ecosystems, but finding evidence for significant and lasting changes to preindustrial landscapes is rare. We report on human-caused changes to the nitrogen cycle in Ireland in the Bronze Age, associated with intensification of agriculture and animal husbandry that resulted in long-term changes to the nitrogen isotope values of animals (wild and domesticates) during the Holocene. Major changes to inputs and cycling of soil nitrogen occurred through deforestation, land clearance and management, and more intensive animal husbandry and cereal crop cultivation in the later Bronze Age; after this time, the Irish landscape took on its current form. Within the debate concerning the onset of the Anthropocene, our data suggest that human activity in Ireland was significant enough in the Bronze Age to have long-term impact, thereby marking a profound shift in the relationship between humans and their environment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.010
GPT teacher head0.243
Teacher spread0.233 · 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.

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

Citations47
Published2018
Admission routes1
Has abstractyes

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