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Record W2488622718 · doi:10.1017/cbo9780511613005.014

Diatoms as indicators of coastal paleoenvironments and relative sea-level change

2010· book-chapter· en· W2488622718 on OpenAlexaff
Luc Denys, Hein de Wolf

Bibliographic record

VenueCambridge University Press eBooks · 2010
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsDiatomGeologyLittoral zoneOceanographyHoloceneClimate changeSea levelSedimentary depositional environmentGlacial periodPhysical geographyPaleontologyGeographyStructural basin

Abstract

fetched live from OpenAlex

Introduction Since nineteenth century naturalists identified salinity as a major determinant of diatom distribution, the remains of these organisms have become popular paleoenvironmental indicators for coastal deposits. A variety of problems in coastal geology were tackled using diatom-based methods, covering fields such as stratigraphy, the study of coastal processes, paleogeography, sea-level and climate change, tectonics, natural hazard assessment and archeology. This review highlights some of the major prospects and problems of paleoenvironmental diatom research on former depositional environments and sedimentation conditions in the coastal zone, as well as its contribution to the study of relative sea-level change and other processes affecting coastal genesis. For several reasons, e.g., the early recognition of important sea-level variations and coastline changes relating to glacial/interglacial cycles, the projected impact of possible future sea-level rise on coastal lowlands, the comparability of the fossil biotic record to contemporaneous observations, and the development of high-resolution dating methods – such research has focused mainly on the Quaternary and the Holocene in particular. Relatively few studies reached further back in time (e.g., Burckle & Akiba, 1978; Harwood, 1986; Pickard et al., 1986; Tawfik & Krebs, 1995). This account therefore also deals primarily with the most recent geological time window, where techniques and applications are most refined. Intended as a brief introduction only, completeness is not attempted. Some closely related topics, such as the ecology of marine–littoral diatoms, salinity calibration, estuarine settings and archeological contexts are treated more in detail elsewhere in this volume.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.031
GPT teacher head0.203
Teacher spread0.172 · 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

Citations58
Published2010
Admission routes1
Has abstractyes

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