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Record W2485691581 · doi:10.2110/pec.08.90.0073

The Role of Ichnology in Refining Shallow Marine Facies Models

2008· book-chapter· en· W2485691581 on OpenAlexaff
James A. MacEachern, Kerrie L. Bann

Bibliographic record

VenueSEPM (Society for Sedimentary Geology) eBooks · 2008
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsIchnologyFaciesGeologyRefining (metallurgy)Marine engineeringPetrologyPaleontologyEngineeringTrace fossilChemistry

Abstract

fetched live from OpenAlex

Abstract The facies characteristics of the shallow marine environment are largely determined by the complex interplay and relative importance of wave energy, tidal flux, storm magnitudes and frequencies, and river-sediment input. Ichnology is a valuable tool in constraining these processes when integrated with sedimentological and stratigraphic analysis. Trace fossils are biogenic sedimentary structures, strongly facies controlled, and generally temporally long ranging, making them ideal for facies analysis. Ichnofossils are also readily observable at outcrop and core scales, making their identification and interpretation as routine as that of primary physical sedimentary structures. The ichnofacies paradigm is exceptionally well poised to offer critical information about the conditions operating during deposition (e.g., softground ichnofacies) or during development of stratigraphic discontinuities (e.g., substrate-controlled ichnofacies and palimpsest softground suites). The ichnofacies concept stands as one of the most elegant but also most widely misunderstood and misused concepts in ichnology. Softground ichnofacies have been refined to include proximal, archetypal, and distal expressions, permitting high-resolution subdivision of depositional environments such as strandline shoreface complexes. Models addressing brackish-water-induced stresses, substrate consistency changes, reduced oxygen levels, and energy variations on bioturbation have enhanced the identification and subdivision of estuarine incised-valley, embayment, and interdistributary-bay deposits. The ichnological characteristics of these brackish-water settings include: (1) suites characterized by reductions in the numbers and diversities of ichnogenera, corresponding to impoverished marine assemblages; (2) traces that are generally diminutive compared to their fully marine counterparts; (3) a predominance of simple opportunistic structures of inferred trophic generalists; (4) suites comprising elements that record variations in substrate consistency and depositional rates; and (5) successions showing locally high degrees of bioturbation, as well as monogeneric trace suites. Ongoing work concentrates on the effects of hypopycnal-induced water turbidity, hyperpycnal discharge, freshets, fluid-mud deposition, heightened depositional rates, and storm events on infaunal behavior, and helps to identify the deltaic ichnological signal, elucidating the relative importance of waves, tides, and fluvial discharge. Generally reduced and sporadically distributed bioturbation intensities, common unburrowed and mud-draped event beds, abrupt juxtaposition of fully marine suites with impoverished suites, predominance of facies-crossing deposit-feeding structures adapted to sandy substrates, and a paucity of dwelling structures attributable to suspension-feeding organisms constitute the recurring ichnological deltaic signal that has been elucidated to date.Ultimately, such models could be applied to along-strike variations in linked depositional systems, enhancing paleogeographicreconstructions.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.195
Teacher spread0.176 · 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 designTheoretical or conceptual
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

Citations216
Published2008
Admission routes1
Has abstractyes

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