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Record W1998372975 · doi:10.1073/pnas.0803634105

Gigantism in unique biogenic magnetite at the Paleocene–Eocene Thermal Maximum

2008· article· en· W1998372975 on OpenAlexaff
Dirk Schumann, Timothy D. Raub, Robert E. Kopp, Jean‐Luc Guerquin‐Kern, Ting‐Di Wu, Isabelle Rouiller, A. V. Smirnov, S. Kelly Sears, Uwe Lücken, Sonia M. Tikoo-Schantz, Reinhard Hesse, Joseph L. Kirschvink, Hojatollah Vali

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGeomagnetism and Paleomagnetism Studies
Canadian institutionsMcGill University
FundersNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsMagnetiteGeologyPaleomagnetismMagnetotactic bacteriaWeatheringMineralogyPaleontologyPhanerozoicGeochemistryCenozoic

Abstract

fetched live from OpenAlex

We report the discovery of exceptionally large biogenic magnetite crystals in clay-rich sediments spanning the Paleocene-Eocene Thermal Maximum (PETM) in a borehole at Ancora, NJ. Aside from previously described abundant bacterial magnetofossils, electron microscopy reveals novel spearhead-like and spindle-like magnetite up to 4 microm long and hexaoctahedral prisms up to 1.4 microm long. Similar to magnetite produced by magnetotactic bacteria, these single-crystal particles exhibit chemical composition, lattice perfection, and oxygen isotopes consistent with an aquatic origin. Electron holography indicates single-domain magnetization despite their large crystal size. We suggest that the development of a thick suboxic zone with high iron bioavailability--a product of dramatic changes in weathering and sedimentation patterns driven by severe global warming--drove diversification of magnetite-forming organisms, likely including eukaryotes.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.023
GPT teacher head0.256
Teacher spread0.233 · 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

Citations83
Published2008
Admission routes1
Has abstractyes

Explore more

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