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Record W1973430117 · doi:10.1029/2007jb005018

Scaling of columnar joints in basalt

2008· article· en· W1973430117 on OpenAlexaff
Lucas Goehring, Stephen W. Morris

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGeologyLavaScalingBasaltIgneous rockRADIUSMechanicsConvectionFracture (geology)AdvectionThermal diffusivityThermalPetrologyGeometryMeteorologyPhysicsGeotechnical engineeringSeismologyVolcanoThermodynamicsGeochemistry

Abstract

fetched live from OpenAlex

We describe field work, analysis, and modeling of columnar joints from the Columbia River Basalt Group. This work is focused on the regions around the Grand Coulee, Snake River, and Columbia Gorge, which form parts of this unusually homogeneous and very large sample of columnar basalt. We examine in detail the scaling relationship between the column width and the size of the striae and relate these quantitatively to thermal and fracture models. We found that the column radius and stria size are proportional to each other and inversely proportional to the cooling rate of the lava. Near a flow margin, our results put observational constraints on diffusive thermal models of joint formation. Deeper than a few meters into a colonnade, our measurements are consistent with a simple advection‐diffusion model of two‐phase convective cooling within the joints, regardless of the direction of cooling. This model allows an accurate comparison of igneous columnar jointing and joints due to desiccation in laboratory analog systems. We also identify a new length scale in which wavy columns can appear in some colonnades. The mechanisms leading to the wavy columns are likely related to those underlying similar wavy cracks in 2‐D analog systems.

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)0.001
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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.050
GPT teacher head0.287
Teacher spread0.238 · 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

Citations129
Published2008
Admission routes1
Has abstractyes

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