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Record W2131538631 · doi:10.2110/palo.2014.032

COMPOSITIONAL FIDELITY OF DEATH ASSEMBLAGES FROM A CORAL REEF-ASSOCIATED TIDAL-FLAT AND SHALLOW SUBTIDAL LAGOON IN THE NORTHERN RED SEA

2015· article· en· W2131538631 on OpenAlexfundno aff
Martin Zuschin, C. Ebner

Bibliographic record

VenuePalaios · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine Biology and Ecology Research
Canadian institutionsnot available
FundersMcGill University
KeywordsGeologyReefOceanographyCoralCoral reefTidal flatFringing reefPaleontologySediment

Abstract

fetched live from OpenAlex

Abstract This study focuses on quantitative analysis of the species composition and distribution of living and dead mollusks to assess fidelity of death assemblages in a protected tidal flat and a shallow subtidal lagoon behind a fringing reef from the Indo-Pacific province. We evaluate how well the death assemblage (DA) reflects the original living community and whether there was a recent ecological shift in species composition. Quantitative analysis of 18 samples from unvegetated sandy substrata shows that dead individuals dominate in the shallow subtidal lagoon, but living and dead individuals were roughly equally abundant on the tidal flat. This difference points to rapid degradation or export of dead shells from tidal flats, leading to smaller potential for time averaging. Rarefied species richness and diversity of DAs is higher than that of the living assemblages (LAs) at the scale of habitats and at the scale of the study area, and this difference in richness is stronger and live-dead (LD) agreement in composition is smaller in the subtidal than in the intertidal habitats. Distinct assemblages characterized intertidal and subtidal habitats both in LAs and DAs, and the rank-abundance distributions of DAs generally corresponded to that of LAs. We suggest that anthropogenic impact in the area did not result in a major environmental change in the subtidal environment during the past few decades because existing small differences between LAs and DAs can be explained by some degree of time averaging and small-scale redistribution of shells. On the tidal flat, however, the lower time-averaging of the DA and the generalistic life habits of prominent members in the LA do not exclude a major shift.

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)0.001
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 score0.148
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.047
GPT teacher head0.263
Teacher spread0.216 · 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

Citations22
Published2015
Admission routes1
Has abstractyes

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