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Record W3011899812 · doi:10.1029/2019jc015703

Sea Level Change Controlled the Sedimentary Processes at the Makran Continental Margin Over the Past 13,000 yr

2020· article· en· W3011899812 on OpenAlexfundno aff
Wei He, Jianguo Liu, Yun Huang, Li Cao

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersChinese Academy of SciencesMinistry of Natural Resources
KeywordsGeologyContinental marginSedimentary rockContinental shelfHoloceneOceanographySea levelPaleontologySedimentPleistoceneTectonics

Abstract

fetched live from OpenAlex

Abstract Climate change, sea level fluctuations, and tectonic uplift play key roles in the evolution of sedimentary systems on continental margins. In the Arabian Sea, the Makran continental margin is suitable for studying these processes during the Holocene due to its high sedimentation rate and continuous sequence of Holocene sediments. Here, high‐resolution clay mineral and grain size analyses have been conducted to better understand the sedimentary process and controlling factors over the past 13,000 yr. The results show that the influence of Indus‐derived sediments on the Makran continent margin is negligible. Holocene relative sea level fluctuations can strongly control the shelf accommodation space due to the narrow shelf, which in turn affects the deposition process at the Makran continental margin. The sediment records at the central Makran continental margin are more suitable for studying ancient earthquakes or tsunamis.

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)0.000
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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.092
GPT teacher head0.316
Teacher spread0.224 · 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

Citations20
Published2020
Admission routes1
Has abstractyes

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