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Record W2883876267 · doi:10.1016/j.dib.2018.07.037

High resolution carbon stock and soil data for three salt marshes along the northeastern coast of North America

2018· article· en· W2883876267 on OpenAlexafffundabout
Lee B. van Ardenne, Serge Jolicoeur, D. Bérubé, David M. Burdick, Gail L. Chmura

Bibliographic record

VenueData in Brief · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsGeological Survey of CanadaUniversité de MonctonMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaNatural Resources CanadaCommission for Environmental Cooperation
KeywordsMarshSalt marshSoil carbonShapefilePeatSoil surveyGeologyDominance (genetics)WetlandEnvironmental scienceHydrology (agriculture)OceanographyPhysical geographyGeographySoil scienceSoil waterEcologyArchaeology

Abstract

fetched live from OpenAlex

The data presented here includes a table of soils measurements taken at high resolution depth intervals (5 cm) for three salt marshes, two along the New Brunswick coast of Canada and one on the southern coast of Maine, USA. The data includes a table which includes the bulk density, percent organic matter, percent organic carbon, carbon stock, and rhizome dominance (if identifiable) at 5 cm depth intervals for each soil core. Shapefiles are also included which indicates the GPS position of acquired cores and sites where marsh depth was measured but no material was recovered. These shapefiles also include marsh peat depth and estimates of carbon stock for each point. For further information and interpretation of the included data please see the companion research article titled "The Importance of Geomorphic Context for Estimating the Carbon Stock of Salt Marshes" [1].

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: Observational · Consensus signal: Observational
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.790
Threshold uncertainty score0.417

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.237
Teacher spread0.212 · 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
GenreDataset

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

Citations6
Published2018
Admission routes3
Has abstractyes

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