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Record W1608446593 · doi:10.5539/enrr.v5n3p19

Assessment of Self-Purification Process of Thi Nai lagoon (Binh Dinh Province, Viet Nam)

2015· article· en· W1608446593 on OpenAlexvenueno aff
Trang Cao Thi Thu, Dieu Luu Van, Thanh Tran Duc, Sinh Le Xuan

Bibliographic record

VenueEnvironment and Natural Resources Research · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsDry seasonWet seasonEnvironmental scienceEnvironmental chemistryPollutantPollutionSedimentationViet namAmmoniumChemistryEcologyBiologySediment

Abstract

fetched live from OpenAlex

Processes related to self-purification of Thi Nai lagoon has been studied in-situ and in laboratory in rainy season (October, 2013) and in dry season (May, 2014). Studied results shows that the capacity of self-purification of Thi Nai lagoon is quite good in rainy season, and the dominated process is material exchange. In dry season, due to the weak of material exchange, there is the accumulation of pollutants in water body, especial for nitrite, ammonium and phosphate. The studied results also indicate that the main processes that dominate the self-purification of Thi Nai lagoon are materials exchange, sedimentation, dispersion, decompose, and photosynthesis, respectively. The pollution loads discharged everyday into the Thi Nai lagoon is high, reducing the self-purification of lagoon, therefore it need to be controlled restrict.

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)0.002
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 score0.136
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.047
GPT teacher head0.356
Teacher spread0.308 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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