MétaCan
Menu
← Back to cohort
Record W3201526697 · doi:10.1029/2021gl094543

Preservation and Destruction of Holocene Marine Terraces: The Effects of Episodic Versus Gradual Relative Sea Level Change

2021· article· en· W3201526697 on OpenAlexaff
Hironori Matsumoto, Mark E. Dickson, Paul S. Kench

Bibliographic record

VenueGeophysical Research Letters · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsSimon Fraser University
FundersMarsden Fund
KeywordsHoloceneTerrace (agriculture)GeologyShorePeninsulaSea levelRiver terracesPhysical geographyCliffOceanographyPeriod (music)WeatheringPaleontologyGeomorphologyFluvialArchaeologyGeography

Abstract

fetched live from OpenAlex

Abstract Holocene marine terraces occur globally and record information about the timing and magnitude of past coseismic events. Staircased terraces develop through repetitive coseismic uplift of shore platforms, but are also subject to destruction from subsequent wave erosion and rock weathering. In this study we calibrate a rock coast evolution model using terrace field data from Mahia Peninsula, New Zealand, and use it to investigate how relative sea level (RSL) change influences Holocene terrace development. Analyses of 10,002 simulations reveal time periods of extremely rapid terrace creation and destruction as a result of shore platform development processes that are modulated both by episodic and gradual RSL change scenarios. Subtle differences in these scenarios give rise to completely different terrace sequences, even if coseismic event timing is held constant. Improved interpretation of Holocene terrace sequences require higher resolution paleo RSL data and chronological data on shore platform development.

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)0.002
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: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.099
GPT teacher head0.312
Teacher spread0.213 · 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

Citations19
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueGeophysical Research Letters→Same topicGeology and Paleoclimatology Research→French-language works237,207→