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Record W2053192104 · doi:10.4141/s04-016

Nitrogen mineralization processes of soils from natural saline-alkalined wetlands, Xianghai National Nature Reserve, China

2005· article· en· W2053192104 on OpenAlexvenueno aff
Junhong Bai, Hua Ouyang, Wei Deng, Qinggai Wang, Hui Chen, Caiping Zhou

Bibliographic record

VenueCanadian Journal of Soil Science · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsnot available
FundersChina Postdoctoral Science FoundationChinese Academy of Sciences
KeywordsWetlandMineralization (soil science)MarshEcosystemSoil waterNitrogenEnvironmental scienceNitrogen cycleEnvironmental chemistryHydrology (agriculture)Organic matterEcologySoil scienceChemistryGeologyBiology

Abstract

fetched live from OpenAlex

Nitrogen mineralization was evaluated using a 12-wk anaerobic incubation at 30°C in two wetland soils located in Xianghai National Nature Reserve, China. The Erbaifangzi wetland is an open wetland because it hydrologically connected to the surrounding ecosystem, whereas the Fulaowenpao wetland is a closed wetland, which is not hydrologically connected. Nitrogen mineralization was fitted to an effective cumulative temperature model. Nitrogen mineralization increased gradually with increases in the cumulative temperature and decreased with depth in the soil profile. Nitrogen mineralization was positively correlated with total N (TN) or soil organic matter (SOM), but not with soil pH. Basal N mineralization was found to be greater in the Fulaowenpao wetland (0 .314g N m-2 d-1) than the Erbaifangzi wetland (0.230 g N m-2 d-1). Key words: Saline-alkalined wetland; marsh soils; nitrogen mineralization; anaerobic incubation; the effective cumulative temperature model

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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

Citations25
Published2005
Admission routes1
Has abstractyes

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