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Record W2187018096

Coastal dune vulnerability among selected Scottish systems

2011· article· en· W2187018096 on OpenAlexaboutno aff
A. T. Williams, R. W. Duck, Michael R. Phillips

Bibliographic record

VenueDiscovery Research Portal (University of Dundee) · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsVulnerability (computing)Vulnerability indexBayGeographyVulnerability assessmentRange (aeronautics)Rating systemEnvironmental sciencePhysical geographyHydrology (agriculture)Environmental resource managementGeologyOceanographyEngineeringComputer scienceArchaeologyGeotechnical engineeringPsychological resiliencePsychologyClimate change
DOInot available

Abstract

fetched live from OpenAlex

Eleven Scottish dune systems were investigated as to their vulnerability with respect to management procedures. Analysis consisted of the structured use of a rating scheme to assess the environmental conditions and range of protection measures at each site. A 54 parameter checklist was utilised to assess Site and Dune Morphology (8 parameters); B) Beach Condition (9); C) Surface Character of the Seaward 200 m of Dune System (12); D) Pressure of Use (14) and E) Recent Protection Measures (11). The percentage of the maximum possible rating for each category was calculated and summation of the 43 parameter ratings A) to D) provides a Vulnerability Index (VI), which ranged from 40% at Gaineamh Mhor to 55% at Calgary Bay. The percentage score for the 11 parameters in category E) gives a Protection Measure Index (PM), which ranged from 18% at Breckon to 73% at Culzean. Systems with a VI/PM ratio in the range 0.8-1.3 are regarded as having an equilibrium relationship between vulnerability and protection; sites with values 1.3 (e.g. Ardalanish) are out of equilibrium (negative), i.e. they are under protected. Alternatively, a descriptive categorisation can be derived: I. Low Vulnerability - Low Management Response; II. High Vulnerability - High Management Response; III. Low Vulnerability - High Management Response; IV. High Vulnerability - Low Management Response. The approaches mentioned improve objectivity in dune vulnerability measurement and provides a useful basis for proactive management.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.234
Teacher spread0.194 · 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.

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

Citations5
Published2011
Admission routes1
Has abstractyes

Explore more

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