MétaCan
Menu
Back to cohort
Record W2129995346 · doi:10.2110/jsr.2009.012

Fine-Grained Versus Coarse-Grained Wave Ripples Generated Experimentally Under Large-Scale Oscillatory Flow

2009· article· en· W2129995346 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Sedimentary Research · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsQueen's UniversityGeological Survey of Canada
FundersU.S. Army Corps of EngineersNatural Sciences and Engineering Research Council of Canada
KeywordsGeologyScale (ratio)Flow (mathematics)MechanicsPhysics

Abstract

fetched live from OpenAlex

Abstract Wave ripples were generated in a wave tunnel under large-scale oscillatory flow (orbital diameter 1–4.5 m) using two different grain sizes, very fine sand and coarse sand. The geometry of bed configurations that were produced varied strongly as a function of grain size: small anorbital ripples (wavelengths ~ 10 cm, heights < 1 cm) formed exclusively in very fine sand at low oscillatory velocities, whereas large orbital ripples (wavelengths 50–350 cm, heights 7–26 cm) formed in both very fine and coarse sand, but were subdued, sharp- to round-crested, and 2-D to 3-D in very fine sand, and steep, sharp-crested, and 2-D in coarse sand. The large ripples in fine sand, if aggraded, would deposit low-angle (5–15°) cross stratification resembling hummocky cross stratification, whereas the large ripples in coarse sand would deposit high-angle (15–25°) cross stratification that might be mistaken for the deposit of a dune because of its high dip angle and large set thickness (> 5 cm). These results support the hypothesis advanced by Leckie (1988) that large waves generate markedly different stratigraphic signatures in fine-grained and coarse-grained sediment.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.057
GPT teacher head0.309
Teacher spread0.252 · 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