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Record W4251102395 · doi:10.1017/cbo9781107296916

Coastal Wetlands of the World

2014· book· en· W4251102395 on OpenAlexaff
David B. Scott, Jennifer Frail-Gauthier, Petra J. Mudie

Bibliographic record

VenueCambridge University Press eBooks · 2014
Typebook
Languageen
FieldEarth and Planetary Sciences
TopicAquatic and Environmental Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsWetlandGeographySalt marshMarshEcologyIntertidal zoneLandscape ecologyGlobeEnvironmental resource managementEnvironmental scienceHabitat

Abstract

fetched live from OpenAlex

Salt marshes and mangrove forests, the intertidal wetlands of the world's coastlines, provide key ecological services to all areas of the globe. This cutting-edge, richly illustrated book introduces the essential elements of coastal wetlands and their applications. The book opens by introducing coastal oceanography, the physical features of wetlands, their ecology, and human impacts upon them, giving all students the necessary background for wetlands studies. It then presents detailed case studies from around the world with extensive illustrations, supplying a wider, global-scale picture of wetlands geomorphology and biodiversity. The final chapters discuss some unique applications of coastal wetlands, including geological monitoring, uses in biotechnology and agriculture, and various experimental mesocosms. This is ideal as supplementary reading to support students on a wide range of earth and life science courses, from environmental science, ecology and palaeoecology to geomorphology and geography. It will also be a valuable interdisciplinary reference for researchers.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.037
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0370.009

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 head0.012
GPT teacher head0.156
Teacher spread0.144 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations48
Published2014
Admission routes1
Has abstractyes

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