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Record W2916106331 · doi:10.1111/sed.12591

Constraining sediment provenance for tsunami deposits using distributions of grain size and foraminifera from the Kujukuri coastline and shelf, Japan

2019· article· en· W2916106331 on OpenAlexaff
Jessica E. Pilarczyk, Yuki Sawai, Dan Matsumoto, Yuichi Namegaya, Naohisa Nishida, Ken Ikehara, Osamu Fujiwara, Chris Gouramanis, Tina Dura, Benjamin P. Horton

Bibliographic record

VenueSedimentology · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsSimon Fraser University
FundersJapan Society for the Promotion of ScienceDivision of Earth SciencesNational Science FoundationEarth Observatory of SingaporeNational Research Foundation SingaporeNational Institute of Advanced Industrial Science and Technology
KeywordsGeologyForaminiferaTaphonomyProvenanceSedimentary depositional environmentSedimentGrain sizeSedimentary rockSubmarine pipelineOceanographyContinental shelfDeposition (geology)PaleontologyGeomorphologyBenthic zone

Abstract

fetched live from OpenAlex

Abstract Tsunami deposits preserved in the geological record provide a more comprehensive understanding of their patterns of frequency and intensity over longer timescales; but recognizing tsunami deposits can prove challenging due to post‐depositional changes, lack of contrast between the deposits and surrounding sedimentary layers, and differentiating between tsunami and storm deposition. Modern baseline studies address these challenges by providing insight into modern spatial distributions that can be compared with palaeotsunami deposits. This study documents the spatial fingerprint of grain size and foraminifera from Hasunuma Beach and the Kujukuri shelf to provide a basis from which tsunami deposits can be interpreted. At Hasunuma Beach, approximately 50 km east of Tokyo, the spatial distribution of three common proxies (foraminiferal taxonomy, foraminiferal taphonomy and sediment grain size) for tsunami identification were mapped and clustered using Partitioning Around Medoids cluster analysis. Partitioning Around Medoids cluster analysis objectively discriminated two coastal zones corresponding to onshore and offshore sample locations. Results show that onshore samples are characterized by coarser grain sizes (medium to coarse sand) and higher abundances of Pararotalia nipponica (27 to 63%) than offshore samples, which are characterized by finer grain sizes (fine to medium sand), lower abundances of Pararotalia nipponica (2 to 19%) and Ammonia parkinsoniana (0 to 10%), higher abundances of planktonics (15 to 58%) and species with fragile tests including Uvigerinella glabra. When compared to grain‐size and foraminiferal taxonomy, foraminiferal taphonomy; i.e. surface condition of foraminifera, a proxy not commonly used to identify tsunami deposits, was most effective in discriminating modern coastal zones (identified supratidal, intertidal and offshore environments) and determining sediment provenance for tsunami deposits at Kujukuri. This modern baseline study assists the interpretation of tsunami deposits in the geological record because it provides a basis for sediment provenance to be determined.

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)0.000
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: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.018
GPT teacher head0.257
Teacher spread0.239 · 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

Citations23
Published2019
Admission routes1
Has abstractyes

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