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Record W1947362175 · doi:10.1038/srep10264

Spheroidal carbonaceous particles are a defining stratigraphic marker for the Anthropocene

2015· article· en· W1947362175 on OpenAlexaff
Graeme T. Swindles, Elizabeth J. Watson, T. Edward Turner, Jennifer M. Galloway, Thomas Hadlari, Jane C. Wheeler, Karen L. Bacon

Bibliographic record

VenueScientific Reports · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsGeological Survey of Canada
FundersNatural Environment Research CouncilAberystwyth University
KeywordsAnthropocenePaleontologyGeologyAstrobiologyEarth scienceComputer scienceBiology

Abstract

fetched live from OpenAlex

There has been recent debate over stratigraphic markers used to demarcate the Anthropocene from the Holocene Epoch. However, many of the proposed markers are found only in limited areas of the world or do not reflect human impacts on the environment. Here we show that spheroidal carbonaceous particles (SCPs), a distinct form of black carbon produced from burning fossil fuels in energy production and heavy industry, provide unambiguous stratigraphic markers of the human activities that have rapidly changed planet Earth over the last century. SCPs are found in terrestrial and marine sediments or ice cores in every continent, including remote areas such as the high Arctic and Antarctica. The rapid increase in SCPs mostly occurs in the mid-twentieth century and is contemporaneous with the 'Great Acceleration'. It therefore reflects the intensification of fossil fuel usage and can be traced across the globe. We integrate global records of SCPs and propose that the global rapid increase in SCPs in sedimentary records can be used to inform a Global Standard Stratigraphic Age for the Anthropocene. A high-resolution SCP sequence from a lake or peatland may provide the much-needed 'Golden Spike' (Global Boundary Stratotype Section and Point).

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)0.003
metaresearch head score (Gemma)0.001
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 score0.044
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.042
GPT teacher head0.268
Teacher spread0.226 · 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

Citations107
Published2015
Admission routes1
Has abstractyes

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