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Record W6996885623

Tidal Marsh Restoration

2014· article· en· W6996885623 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of New Hampshire Scholars Repository (University of New Hampshire at Manchester) · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSalt marshMarshWildlifeRestoration ecologyFlood controlLimitingWork (physics)Flood mythEcosystem
DOInot available

Abstract

fetched live from OpenAlex

Many coastal tidal marshes have been significantly degraded by roadways and other projects that restrict tidal flows, limiting their ability to provide vital ecosystem services including support of fish and wildlife populations, flood protection, water quality maintenance, and open space. Tidal Marsh Restoration provides the scientific foundation and practical guidance necessary for coastal zone stewards to initiate salt marsh tidal restoration programs. The book compiles, synthesizes, and interprets the current state of knowledge on the science and practice of salt marsh restoration, bringing together leaders across a range of disciplines in the sciences (hydrology, soils, vegetation, zoology), engineering (hydraulics, modeling), and public policy, with coastal managers who offer an abundance of practical insight and guidance on the development of programs. The work presents in-depth information from New England and Atlantic Canada, where the practice of restoring tidal flow to salt marshes has been ongoing for decades, and shows how that experience can inform restoration efforts around the world. Students and researchers involved in restoration science will find the technical syntheses, presentation of new concepts, and identification of research needs to be especially useful as they formulate research and monitoring questions, and interpret research findings. Tidal Marsh Restoration is an essential work for managers, planners, regulators, environmental and engineering consultants, and others engaged in planning, designing, and implementing projects or programs aimed at restoring tidal flow to tide-restricted or diked salt marshes.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.025
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0250.006

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 head0.009
GPT teacher head0.169
Teacher spread0.160 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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