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Record W2105640096 · doi:10.1017/s0016756802006830

Bio-signatures in metabasaltic glass of a Caledonian ophiolite, West Norway

2002· article· en· W2105640096 on OpenAlexaff
Harald Furnes, Karlis Muehlenbachs, Terje Torsvik, Ole Tumyr, Shi Lang

Bibliographic record

VenueGeological Magazine · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOphiolitePillow lavaGeologyGeochemistryMetamorphismOceanic crustOrganic matterGreenschistBasaltMineralogyVolcanic rockVolcanoChemistryPaleontologySubduction

Abstract

fetched live from OpenAlex

Evidence of bioalteration of natural basaltic rocks, presently receiving much attention, has so far been restricted to in situ oceanic crust and ophiolites in which fresh glass is still present. Here we present evidence of preserved bio-signatures in the chilled margin of pillow lavas of an old (443 Ma) ophiolite that has suffered pervasive lower greenschist facies metamorphism and deformation. X-ray mapping of initial alteration zones shows the remains of organic carbon associated with highly-concentrated Fe and S. Bioproduction of CO2 is further reflected in the low δ13C values of calcite extracted from pillow rims, compatible with microbe-induced fractionation during oxidation of organic matter. We attribute these effects to growth of sulphate-reducing bacteria at the early stage of ophiolite formation. During energy metabolism these bacteria reduce sulphate to H2S and oxidize organic matter to CO2 . Hydrogen sulphide will eventually react with iron and form pyrite, and carbon dioxide is precipitated as calcium carbonate. The results of this study may thus trigger the search for bio-signatures in glassy volcanic rocks of any age.

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 score0.085
Threshold uncertainty score0.170

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 communication0.0000.000
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 head0.026
GPT teacher head0.238
Teacher spread0.212 · 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

Citations25
Published2002
Admission routes1
Has abstractyes

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