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Record W2074881970 · doi:10.1017/s0016756803007830

Changes in organic matter production and accumulation as a mechanism for isotopic evolution in the Mesoproterozoic ocean

2003· article· en· W2074881970 on OpenAlexaboutno aff
Tracy D. Frank, Linda C. Kah, Timothy W. Lyons

Bibliographic record

VenueGeological Magazine · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Stratigraphy of Fossils
Canadian institutionsnot available
Fundersnot available
KeywordsBiosphereIsotopes of carbonTotal organic carbonOrganic matterGeologyδ13CArcticPaleontologyEarth sciencePrecambrianAnoxic watersOceanographyEcologyStable isotope ratioChemistryEnvironmental chemistryBiology

Abstract

fetched live from OpenAlex

Mesoproterozoic marine successions worldwide record a shift in average δ13C values from 0 to +3.5‰, with the latter value evident in successions younger than 1250 Ma. New carbon isotope data from the ∼1300 to 1270 Ma Dismal Lakes Group, Arctic Canada, provide further insight into this fundamental transition. Data reveal that the shift to higher δ13C values was gradual and marked by occasional excursions to values less than 0‰. When compared to records from older and younger marine successions, it is evident that the difference between isotopic minima and maxima increased with time, indicating that the marine system evolved to become isotopically more variable. We interpret these patterns to record an increase in the crustal inventory of organic carbon, reflecting eukaryotic diversification and a change in the locus of organic carbon burial to include anoxic deep marine sites where preservation potential was high. We speculate that the release of O2 to Earth's surface environments associated with increased organic carbon storage induced irreversible changes in the Mesoproterozoic biosphere, presaging the more extreme environmental and evolutionary developments of the Neoproterozoic.

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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.025
GPT teacher head0.243
Teacher spread0.218 · 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

Citations69
Published2003
Admission routes1
Has abstractyes

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