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Record W2091675572 · doi:10.1080/01490419.2011.637851

GIS-Based Analysis and Modeling of Coastline Advance and Retreat Along the Coast of Guyana

2012· article· en· W2091675572 on OpenAlex
Sajid Rashid Ahmad, V. Chris Lakhan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMarine Geodesy · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsShoreGeologyAccretion (finance)GeographyPhysical geographyCoastal erosionErosionDigital elevation modelSedimentRemote sensingGeographic information systemCartographyOceanographyGeomorphology

Abstract

fetched live from OpenAlex

This research utilized a Geographical Information System (GIS)-based approach to analyze, map and model coastline advance and retreat. A time series (1941–1987) of empirical advance and retreat data from the coast of Guyana was used. Coastlines were also extracted from 1987, 1990 and 1992 Landsat TM images, and 1999, 2002, 2004 and 2006 Landsat ETM+ images. The historical data were used to calculate advance and retreat (AOR) rates and sediment volume changes. Distinct periods of advance and retreat matched corresponding periods of sediment gains and losses. The Digital Shoreline Analysis System (DSAS) was used to predict rates of coastline change. Graphical plots of DSAS results identified spatial and temporal phase shifts of the coastline. Recurring episodes of accretion and erosion could be associated with the presence or absence of mudbanks along the coast.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score0.971

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)0.0000.000

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 head0.010
GPT teacher head0.210
Teacher spread0.200 · 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