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Record W4200196757 · doi:10.51835/bsed.2021.47.3.360

The Palaeo-Kambaniru river mouth, Sumba, East Nusa Tenggara, Indonesia: A record of strongly seasonal catastrophic flow in a monsoon-controlled deltaic complex

2021· article· en· W4200196757 on OpenAlexafffund
John‐Paul Zonneveld, Yahdi Zaim, Yan Rizal, Aswan Aswan, A.R. Fortuin, Roy Larick, Russell L. Ciochon

Bibliographic record

VenueBerita Sedimentologi · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaNational Geographic Society
KeywordsGeologyReefFluvialPaleontologyCoral reefTerrace (agriculture)ConglomeratePleistoceneEcological successionRiver terracesDeltaGeomorphologyOceanographySedimentary rockArchaeologyStructural basinGeography

Abstract

fetched live from OpenAlex

The Kambaniru River valley near the city of Waingapu preserves a thick succession of coarse-grained fluvial-deltaic sediment deposited during the Late Pleistocene. This succession incises through a thick uplifted coral reef terrace succession and records intervals of highly episodic flow events during the last glacial interval. The occurrence of intraclastic, coarse sand/gravel matrix olistostromes in several areas attests to the occasionally catastrophic nature of flow in the ancestral Kambaniru River. Small to moderate-sized coral-rich reefs and laterally restricted reef terraces occur on delta-front conglomerate successions at multiple horizons through the study interval. These reefs record both intervals of low flow as well as periodic river-mouth avulsion episodes. Comparison of radiometric dates obtained from pelecypod and coral material from both deltaic successions and laterally adjacent coral reef terrace intervals indicates that uplift/subsidence history of the terraces differs from that of the valley and that correlation between the two should be taken with care.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.673

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.022
GPT teacher head0.210
Teacher spread0.189 · 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 teacher head, 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

Citations0
Published2021
Admission routes2
Has abstractyes

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