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Record W2168689508 · doi:10.4319/lo.2008.53.4.1468

Compound‐specific stable isotopes of organic compounds from lake sediments track recent environmental changes in an alpine ecosystem, Rocky Mountain National Park, Colorado

2008· article· en· W2168689508 on OpenAlexaff
Sara K. Enders, Mark Pagani, Silvio Pantoja, Jill S. Baron, Alexander P. Wolfe, Nikolai Pedentchouk, Lilianna Nunez

Bibliographic record

VenueLimnology and Oceanography · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEnvironmental scienceEcologyAlgaeIsotopes of nitrogenHydrology (agriculture)OceanographyGeologyNitrogenChemistryBiology

Abstract

fetched live from OpenAlex

Compound‐specific nitrogen, carbon, and hydrogen isotope records from sediments of Sky Pond, an alpine lake in Rocky Mountain National Park (Colorado, United States of America), were used to evaluate factors contributing to changes in diatom assemblages and bulk organic nitrogen isotope records identified in lake sediments across Colorado, Wyoming, and southern Montana. Nitrogen isotopic records of purified algal chlorins indicate a substantial shift in nitrogen cycling in the region over the past ~60 yr. Temporal changes in the growth characteristics of algae, captured in carbon isotope records in and around Sky Pond, as well as a ‐60‰ excursion in the hydrogen isotope composition of algal‐derived palmitic acid, are coincident with changes in nitrogen cycling. The confluence of these trends is attributed to an increase in biologically available nitrogenous compounds caused by an expansion of anthropogenic influences and temporal changes in catchment hydrology and nutrient delivery associated with meltwater dynamics.

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)0.000
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 score0.150
Threshold uncertainty score0.299

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.023
GPT teacher head0.218
Teacher spread0.195 · 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

Citations44
Published2008
Admission routes1
Has abstractyes

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