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Record W2255056010 · doi:10.1002/esp.3886

Influence of lithostratigraphy on the retreat of an unconsolidated sedimentary coastal cliff (St. Lawrence estuary, eastern Canada)

2015· article· en· W2255056010 on OpenAlexafffundabout
Gabriel Joyal, Patrick Lajeunesse, Antoine Morissette, Pascal Bernatchez

Bibliographic record

VenueEarth Surface Processes and Landforms · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversité du Québec à RimouskiUniversité LavalCenter for Northern Studies
FundersUniversité du Québec à Rimouski
KeywordsGeologyCliffLithostratigraphyEstuaryShoreSedimentary rockCoastal erosionPalaeogeographyOceanographyGeomorphologyPaleontologyTectonicsVolcanism

Abstract

fetched live from OpenAlex

Abstract This paper investigates the processes involved in unconsolidated cliff recession using LiDAR surveys (2005, 2010 and 2013) and aerial photographs (1964–2012) at Pointe‐au‐Bouleau, on the north shore of the St. Lawrence estuary, in eastern Canada. The high lithostratigraphic variability of the sediments allowed for the identification of stratigraphic and lithological variables that explain the evolution of coastal cliffs. Space‐for‐time substitution was also used to assess how lithostratigraphy controls the evolution of emerged glaciomarine coastal cliffs over decadal to centennial timescales. This case study presents new quantitative data that contributes to a better understanding of the role of sediment architecture, stratigraphy and geomorphology on coastal evolution. The methodological approach includes the development of a new conceptual model suitable for identifying erosion on cliff coastlines. The high spatial resolution methodology (<5 cm) used herein demonstrates the need for further research using LiDAR data in order to quantify the processes involved in the evolution of coastal cliffs. Copyright © 2015 John Wiley & Sons, Ltd.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.626
Threshold uncertainty score0.843

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 head0.018
GPT teacher head0.227
Teacher spread0.209 · 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

Citations12
Published2015
Admission routes3
Has abstractyes

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