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Record W2979623671 · doi:10.5539/enrr.v9n4p1

The First Steps in Examining of Carbon Absorption and Nutrient Salt Filtering Capability of Rhodomelaceae Laurencia Papillosa Seaweed over Some Typical Island Communes in Vietnam Coastal Area

2019· article· en· W2979623671 on OpenAlexvenueno aff
Le Xuan Sinh, Tran Van Phuong, Lê Văn Nam

Bibliographic record

VenueEnvironment and Natural Resources Research · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and Coastal Ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsNutrientRhodomelaceaeGeographyAlgaeBiomass (ecology)Viet namEcologyBiology

Abstract

fetched live from OpenAlex

Viet Hai is a commune in Cat Hai district, Hai Phong City. The commune is located in the East of Cat Ba island which is the third largest island in Vietnam. Nhon Chau is also an island commune which is located in Quy Nhon city, Binh Dinh province. Nam Du commune is one of four island communes of Kien Hai district, Kien Giang province, and located at 120 kilometers away from the Rach Gia city. The results showed that the averaged values of nutrients absorbed by Rhodomelaceae Laurencia Papillosa in 12 hours were 1.39µg/l/day (N-NO2-); 11.74µg/l/day (N-NO3-); 24.08µg/l/day (N-NH4+); and 7.83µg/l/day (P-PO43-) in Viet Hai commune. In Nhon Chau island commune, the averaged values of nutrients absorbed in 12 hours were 1.25µg/l/day (N-NO2-); 7.44µg/l/day (N-NO3-); 11.81µg/l/day (N-NH4+); 23.53µg/l/day (P-PO43-), respectively. In Nam Du island commune, the nutrients absorbed in 12 hours reached the values of 23.4µg/l/day (N-NO2-); 15.3µg/l/day (N-NO3-); 101.65µg/l/day (N-NH4+); 30.32µg/l/day (P-PO43-), respectively. The average values of carbon absorbed by seaweed biomass in Viet Hai, Nhon Chau, and Nam Du communes were 30.27mgC/m2/h, 31.31mgC/m2/h, 33.00mgC/m2/h, respectively.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.001
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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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.

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
Published2019
Admission routes1
Has abstractyes

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