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Record W2063297351 · doi:10.1126/science.1212267

A Coherent Signature of Anthropogenic Nitrogen Deposition to Remote Watersheds of the Northern Hemisphere

2011· article· en· W2063297351 on OpenAlexaff
Gordon W. Holtgrieve, Daniel E. Schindler, William O. Hobbs, Peter R. Leavitt, Eric J. Ward, Lynda Bunting, Guangjie Chen, Bruce P. Finney, Irene Gregory‐Eaves, Sofia Holmgren, Mark J. Lisac, Peter J. Lisi, Koren R. Nydick, Lauren A. Rogers, Jasmine E. Saros, Daniel T. Selbie, Mark D. Shapley, Patrick Walsh

Bibliographic record

VenueScience · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of AlbertaFisheries and Oceans CanadaMcGill UniversityUniversity of Regina
Fundersnot available
KeywordsSignature (topology)Deposition (geology)Northern HemisphereEnvironmental scienceNitrogenNitrogen cycleRemote sensingEnvironmental chemistryPhysical geographyGeographyAtmospheric sciencesGeologyChemistryGeomorphology

Abstract

fetched live from OpenAlex

Humans have more than doubled the amount of reactive nitrogen (Nr) added to the biosphere, yet most of what is known about its accumulation and ecological effects is derived from studies of heavily populated regions. Nitrogen (N) stable isotope ratios ((15)N:(14)N) in dated sediments from 25 remote Northern Hemisphere lakes show a coherent signal of an isotopically distinct source of N to ecosystems beginning in 1895 ± 10 years (±1 standard deviation). Initial shifts in N isotope composition recorded in lake sediments coincide with anthropogenic CO(2) emissions but accelerate with widespread industrial Nr production during the past half century. Although current atmospheric Nr deposition rates in remote regions are relatively low, anthropogenic N has probably influenced watershed N budgets across the Northern Hemisphere for over a 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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.915

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.235
Teacher spread0.215 · 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.

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

Citations361
Published2011
Admission routes1
Has abstractyes

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