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Record W2385538839

Hydrogeochemical characteristics in the arsenic poisoning area in western Jilin Province

2009· article· en· W2385538839 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Quality and Pollution
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsArsenicGroundwaterEnvironmental chemistryArsenic contamination of groundwaterArsenic poisoningField surveyChemistryAquiferEnvironmental scienceMineralogyHydrology (agriculture)GeologyGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

Supported by field survey and sample test data,the SPSS is applied to analyze the relationship between arsenic concentration and chemical components.The results show that the total arsenic concentration is directly proportional to contents of Fe,HCO_3~-,Mn,Cl,PO_4~(3-) and TDS,and inversely proportional to contents of SO_4~(2-) and Se.By studying the hydrochemical conditions and integrating the quantitative relationship,the hydrogeochemical characteristics in the study area is summarized.The specific hydrogelogical characteristic in poisoning area is as follows: arsenic content in groundwater varies with different water type.It is found that the total arsenic concentration is the lowest in HCO_3—Ca type water and the highest in Cl·HCO_3—Na type water.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.353

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 science0.0000.000
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 head0.013
GPT teacher head0.232
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

Quick stats

Citations7
Published2009
Admission routes1
Has abstractyes

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