MétaCan
Menu
Back to cohort
Record W4390461839 · doi:10.1672/ucrt083-265

Marsh Restoration Using Thin Layer Sediment Addition: Initial Soil Evaluation

2017· article· en· W4390461839 on OpenAlexfundno aff
Jacob Berkowitz

Bibliographic record

VenueWetland Science and Practice · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsnot available
FundersEngineer Research and Development CenterU.S. Army Corps of EngineersNature ConservancyBayer CanadaNew Jersey Department of Environmental Protection
KeywordsMarshWetlandSedimentEnvironmental scienceErosionSalt marshLand reclamationStormHydrology (agriculture)DredgingLand degradationLand useGeologyOceanographyGeomorphologyEcologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Many coastal wetlands display degradation attributable to various factors including land development, erosion, salinization, and a lack of sediment inputs. Additionally, conditions may worsen as impacts associated with sea level rise as well as increases in storm frequency and intensity exacerbate marsh stressors

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.004
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.353
Teacher spread0.283 · 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 designSimulation or modeling
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

Citations13
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueWetland Science and PracticeSame topicCoastal wetland ecosystem dynamicsFrench-language works237,207