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Record W4317600350 · doi:10.1130/g50658.1

Unravelling biotic versus abiotic processes in the development of large sulfuric-acid karsts

2023· article· en· W4317600350 on OpenAlexaff
Dimitri Laurent, Guillaume Barré, Christophe Durlet, Pierre Cartigny, Cédric Carpentier, Guillaume Paris, Pauline Collon, Jacques Pironon, Éric C. Gaucher

Bibliographic record

VenueGeology · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicKarst Systems and Hydrogeology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsKarstAbiotic componentCaveSulfuric acidSulfurGeologySulfateCarbonateGeochemistryEnvironmental chemistryMineralogyEarth scienceEcologyChemistryPaleontologyBiologyInorganic chemistry

Abstract

fetched live from OpenAlex

Abstract In carbonate rocks, natural production of sulfuric acid can form karstic cavities. Where both epigenic and hypogenic speleogeneses have taken place, these processes are challenging to constrain, especially if there is more than one source of sulfur involved. Thanks to an innovative approach coupling geomorphology with measurements of multiple sulfur, oxygen, and strontium isotopes, our study of two French Pyrenean caves quantifies the relative influence of both microbial and thermochemical processes implied in sulfuric-acid production. Multiple sulfur isotopes reveal that sulfate speleothems derived from a mixing of microbial H2S in hydrothermal water and fossil thermochemical H2S previously trapped within the cave host rock. We quantify the percentages of biotic and abiotic sulfuric-acid speleogeneses that have taken place in these caves, paving the way for similar studies of other sulfuric-acid caves where usually only microbial activity has been considered.

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 score0.017
Threshold uncertainty score0.034

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 science0.0000.001
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 head0.032
GPT teacher head0.252
Teacher spread0.220 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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