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Coastal foraminifera from the Iranian coast of Makran, Oman Sea (Chabahar Bay to Gawater Bay) as an indicator of tsunamis

2019· article· en· W2898952250 on OpenAlexaff
Seyed Hamid Vaziri, Eduard G. Reinhart, Jessica E. Pilarczyk

Bibliographic record

VenueGeopersia · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsForaminiferaOceanographyGeologyBayIntertidal zoneOverwashProvenanceSupralittoral zonePaleontologyBarrier islandShore

Abstract

fetched live from OpenAlex

Extreme coastal inundation associated with the 2004 Indian Ocean and 1945 Makran tsunamigenic-earthquakes highlight the risk of tsunamis to coastlines of the northern Oman Sea. Foraminifera have been used as indicators of paleotsunamis in the past where allochthonous tests, found in low-energy environments such as in coastal lagoons, ponds, and marshes, indicate marine overwash. In this study, we constrain the modern distributions of foraminifera from coastal Iran so that they may be used to identify and interpret (e.g. assess provenance) paleotsunami deposits in the geologic record. We collected surface sediment samples from sixteen sites within the study area from Chabahar to Gawater Bays on the Makran coast of Iran, selecting locations impacted by the 1945 Makran tsunami. Foraminifera obtained from these locations are dominated by intertidal, subtidal, and supratidal species, with minor abundances of planktic taxa. Samples collected from study locations are characterized by abundances of iron-stained and heavily corroded (e.g. edge rounded and pitted) individuals. Cluster analysis was used to determine three foraminiferal assemblages within the Makran coastal zone: subtidal, intertidal and supratidal. Characterizing modern distributions of foraminifera along the Makran coast of Iran will aid in identifying the provenance of older overwash deposits previously identified in this region

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.011
GPT teacher head0.208
Teacher spread0.197 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2019
Admission routes1
Has abstractyes

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