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Record W2554564763 · doi:10.1144/sp448.15

The origin and occurrence of subaqueous sedimentary cracks

2016· article· en· W2554564763 on OpenAlexaff
Sean McMahon, Ashleigh v.S. Hood, Duncan McIlroy

Bibliographic record

VenueGeological Society London Special Publications · 2016
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsGeologySedimentary rockGeochemistrySedimentary structuresGeomorphologySedimentary depositional environment

Abstract

fetched live from OpenAlex

Abstract The rock record attests that sediments have cracked at or below the sediment–water interface in strictly subaqueous settings throughout Earth history. In recent decades, a number of hypotheses have been advanced to explain this phenomenon, but these are widely regarded as being mutually exclusive and there is little consensus about which model is correct. In this paper, we first review the geometries, lithologies and range of facies in which subaqueous sedimentary cracks occur in the geological record, with particular attention to cracks in carbonates. We then evaluate current models for subaqueous cracking, emphasizing that different models may be correct with respect to different sets of cracks, but that cracking is generally a two-step process involving sediment stabilization prior to disruption. We also present the results of some simple new experiments designed to test the dominant models of crack formation. These results demonstrate for the first time that microbial mats can produce thin, shallow cracks at the sediment–water interface. We conclude that the presence of cracks in marine, brackish and lacustrine rocks should not be used uncritically to infer fluctuations in salinity in the depositional environment. Supplementary material: A video showing a micro-CT scan of a hand-sample from the Monteville Formation, South Africa is available at https://doi.org/10.6084/m9.figshare.c.3580673

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.016
GPT teacher head0.236
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations52
Published2016
Admission routes1
Has abstractyes

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