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Record W2095664253 · doi:10.2110/jsr.2007.073

Up-Estuary Variation of Sedimentary Facies and Ichnocoenoses in an Open-Mouthed, Macrotidal, Mixed-Energy Estuary, Gomso Bay, Korea

2007· article· en· W2095664253 on OpenAlexafffund
Bo Yang, Robert W. Dalrymple, Murray K. Gingras, Sung‐Min Chun, Hee Jun Lee

Bibliographic record

VenueJournal of Sedimentary Research · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsQueen's UniversityGeological Survey of CanadaUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaKorea Institute of Geoscience and Mineral Resources
KeywordsEstuaryGeologyBayFaciesOceanographySedimentary rockGeochemistryGeomorphology

Abstract

fetched live from OpenAlex

Abstract Integrated sedimentologic and ichnologic studies from the open-mouthed, Gomso Bay estuary on the western Korean coast have revealed that both tides and waves play an important role in estuarine sedimentation. Because of up-estuary decrease in wave energy, physical structures pass up-estuary from wave-dominated planar lamination and hummocky cross-stratification to tide-dominated heterolithic stratification. The infaunal distribution is sensitive to physiological stresses, and traces increase in size from the inner bay to the outer bay. The mappable trends in sedimentary facies and ichnofacies appear to be oblique to the estuarine margin in the outer and middle bays because of wave refraction, whereas facies belts in the inner bay are parallel to the estuary margin, reflecting tide-dominated conditions. Although useful estuarine facies models have been constructed from a growing number of modern and ancient studies, the estuarine classification schemes based on tidal range and geomorphic elements are apparently in conflict. Modern examples from Willapa Bay and this study confirm that the facies-belt model should be considered to be the most useful in applying the estuarine classification, and estuary morphology is related directly to the tidal prism rather than tidal range. In this context, the study results can be used to make interpretations of the geometry of coastlines and clastic reservoirs in ancient examples.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.059
GPT teacher head0.336
Teacher spread0.277 · 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.

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

Citations42
Published2007
Admission routes2
Has abstractyes

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