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Preparation of Yangtze River Delta Sediment Reference Materials

2017· article· en· W6906286719 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
Fundersnot available
KeywordsCertified reference materialsSedimentDeltaEstuaryYangtze riverPollutionRiver deltaQuality assurance

Abstract

fetched live from OpenAlex

More than 10 harbour and estuarine sediment reference materials have been developed in the United States, Canada and other countries, but most of them focus on organic pollutants and radionuclide, and lack certified values. Three sediment reference materials of the Yellow river delta have been prepared in China in 2007. In order to meet the needs of offshore marine sediment geochemical surveys and resource exploration, two sediment standard materials of the Yangtze river delta were prepared according to ISO guidelines and technical standards for reference standards at the national level. Two samples were collected according to different particle sizes, and were dried and ball milled to 200 mesh. Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) and Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES) were used to test the homogeneity. Results show that the F values for the variance test were less than the threshold, which indicates good homogeneity. X-ray Fluorescence Spectroscopy was used for a four-time stability test in two years. No statistically significant changes were observed and the stability of the samples was good. A total of 13 accurate and reliable analytical methods were used in 12 technologically significant laboratories to finalize the contents of 53 elements. The major elements show gradient distribution with 16.42% and 11.48% of Al2O3. These two reference materials have multiple elements with determined values by accurate and reliable methods, which can provide quality assurance for the analysis and testing during geological and environmental surveys in the Delta region.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.251
GPT teacher head0.552
Teacher spread0.301 · 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 designBench or experimental
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
Published2017
Admission routes1
Has abstractyes

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