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Record W2111314385 · doi:10.2112/si_69_6

The Physical Condition of South Carolina Beaches 1980–2010

2013· article· en· W2111314385 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Coastal Research · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsnot available
FundersCanada Excellence Research Chairs, Government of Canada
KeywordsOverwashBarrier islandInletBeach nourishmentCoastal erosionShoreBermShoalPlageGeologyLongshore driftErosionOceanographyHydrology (agriculture)South carolinaSalt marshMarshAccretion (finance)Littoral zoneSediment transportWetlandSedimentGeomorphologyEcologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Kana, T.W.; Traynum, S.B.; Gaudiano, D.; Kaczkowski, H.L., and Hair, T., 2013. The physical condition of South Carolina beaches 1980–2010.Thirty years of monitoring surveys and shoreline erosion studies (1980–2010) along the South Carolina coast show that artificial beach nourishment and the natural process of inlet shoal bypassing have advanced the shoreline along most of the developed beaches and barrier islands. Of the ∼98 mi (∼161 km) of developed beaches (including public parks), fully 80% were much healthier in 2010 than in 1980, as evidenced by burial of seawalls, wider berms, and higher dunes. About 15% of the developed beaches are in approximately the same condition as in 1980; the remaining ∼5% are considered in worse condition. The balance of South Carolina beaches (∼89 mi, ∼146 km) are principally wilderness areas with limited public access. The dominant condition of wilderness beaches is high erosion; limited new sand inputs, particularly via inlet bypassing; and accelerated recession as many of these sand-starved beaches wash over salt-marsh deposits. High erosion results from a combination of sand losses to the lagoon, winnowing of muddy marsh deposits outcropping across the receding beach, and longshore transport losses to the adjacent inlet. An estimated 75% of the undeveloped beaches in 2010 were well landward of their 1980 positions. Between 1980 and 2010, ∼39.4 million yd3 (∼30.1 million m3) of beach nourishment from external sources was added to developed and park beaches (∼62.6 mi, ∼102.6 km). This is equivalent to an addition of ∼168 ft (∼51 m) of beach width in the nourished areas. Natural shoal bypassing events appear to have added a similar magnitude of new sand along accreting beaches. Bypassing events at some beaches involved ∼2–5 million yd3 (1.5–3.8 million m3). Ebb dominance at many South Carolina inlets is shown to play an important role in preserving the littoral sand budget, maintaining large sand reservoirs for bypassing and helping maintain the developed beaches in the state. Low rates of erosion in other areas, such as the Grand Strand, combined with large-scale nourishment have advanced those beaches well beyond historic conditions.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.315

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 integrity0.0000.001
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 head0.035
GPT teacher head0.299
Teacher spread0.264 · 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