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Record W2335442799 · doi:10.1061/40876(209)16

Circulation and Variability over the Meso-American Barrier Reef System: Application of a Triply Nested Ocean Circulation Model

2006· article· en· W2335442799 on OpenAlexaff
Jinyu Sheng

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsDalhousie University
Fundersnot available
KeywordsNested set modelClimatologyCirculation (fluid dynamics)Ocean currentSea surface temperatureGeneral Circulation ModelGeologyReefOceanographyEnvironmental scienceClimate change

Abstract

fetched live from OpenAlex

A triply nested-grid ocean circulation modeling system is used to simulate the circulation and associated seasonal variability on the Meso-American Barrier Reef System (MBRS) of the northwest Caribbean Sea. The nested-grid system consists of three subcomponents: a coarse-resolution outer model of the western Caribbean Sea (WCS); an intermediate-resolution middle model of the southern Meso-American Barrier Reef System; and a fine-resolution inner model of the Belizean shelf. The two-way nesting technique based on the smoothed semi-prognostic method developed by Sheng et al. (2005) is used to exchange information between the three subcomponents of the system. The nested-grid system is forced by 12-hourly NCEP wind and climatological monthly mean sea surface heat and freshwater fluxes and integrated for 11 years from 1990 to 2000. Model results of the last 10 years are used to calculate the monthly mean currents, temperature/salinity distributions and associated variability over the MBRS. Model results demonstrate that the circulation has significant temporal and spatial variability in the study 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 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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.369

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.005
GPT teacher head0.184
Teacher spread0.180 · 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 designSimulation or modeling
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

Citations1
Published2006
Admission routes1
Has abstractyes

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