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Record W1974045653 · doi:10.1126/science.1258410

Low Mid-Proterozoic atmospheric oxygen levels and the delayed rise of animals

2014· article· en· W1974045653 on OpenAlexaff
Noah J. Planavsky, Christopher T. Reinhard, Xiangli Wang, Danielle Thomson, Peter McGoldrick, R H Rainbird, Thomas M. Johnson, Woodward W. Fischer, Timothy W. Lyons

Bibliographic record

VenueScience · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsGeological Survey of CanadaCarleton University
Fundersnot available
KeywordsProterozoicPhanerozoicAtmospheric oxygenPrecambrianBiogeochemical cycleContext (archaeology)GeologySedimentary depositional environmentEarth sciencePaleontologyOxygenCenozoicEnvironmental chemistryChemistryStructural basin

Abstract

fetched live from OpenAlex

The oxygenation of Earth's surface fundamentally altered global biogeochemical cycles and ultimately paved the way for the rise of metazoans at the end of the Proterozoic. However, current estimates for atmospheric oxygen (O2) levels during the billion years leading up to this time vary widely. On the basis of chromium (Cr) isotope data from a suite of Proterozoic sediments from China, Australia, and North America, interpreted in the context of data from similar depositional environments from Phanerozoic time, we find evidence for inhibited oxidation of Cr at Earth's surface in the mid-Proterozoic (1.8 to 0.8 billion years ago). These data suggest that atmospheric O2 levels were at most 0.1% of present atmospheric levels. Direct evidence for such low O2 concentrations in the Proterozoic helps explain the late emergence and diversification of metazoans.

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 score0.009
Threshold uncertainty score0.019

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.013
GPT teacher head0.251
Teacher spread0.238 · 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

Citations760
Published2014
Admission routes1
Has abstractyes

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