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Wetland Biogeography

2017· other· en· W4246019054 on OpenAlexaff
Joe R. Melton

Bibliographic record

VenueInternational Encyclopedia of Geography · 2017
Typeother
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsWetlandMarshSwampEnvironmental scienceHabitatEcosystemPeatSalt marshMangroveEcologyWater qualityHydrology (agriculture)GeographyGeologyBiology

Abstract

fetched live from OpenAlex

Wetlands are a unique ecosystem adapted to conditions of saturated soils that connect upland and deep‐water ecosystems. Wetlands cover about 5–8% of the Earth's surface, but are disproportionately important in providing unique habitats for large numbers of plant and animal species, storing immense amounts of carbon, and providing ecosystem services such as flood mitigation, water quality improvement, and coastal protection. Despite the great benefits of wetlands, they have been heavily impacted by human land use with approximately 50% of wetlands in populated regions drained, degraded, or filled in for purposes such as agriculture, mosquito control, forestry, or settlement. Wetlands can be difficult to categorize with some ambiguity in terms used, however, they are generally divided into three groups: coastal wetlands (including saltwater marshes, tidal freshwater marshes, and mangrove swamps), freshwater marshes and swamps, and peatlands (including bogs and fens).

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.508
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.001

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 head0.004
GPT teacher head0.214
Teacher spread0.210 · 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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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