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Record W4408734449 · doi:10.1007/978-981-96-2520-8_16

Certified Reference Material of Trace Elements in Seawater, NMIJ CRM 7204-a

2025· book-chapter· en· W4408734449 on OpenAlexaboutno aff
Yanbei Zhu

Bibliographic record

VenueSpringer oceanography · 2025
Typebook-chapter
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsnot available
Fundersnot available
KeywordsSeawaterCertificationCertified reference materialsTRACE (psycholinguistics)Environmental chemistryEnvironmental scienceChemistryGeologyOceanographyChromatographyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Abstract A certified reference material (CRM) for the determination of trace elements in seawater samples was developed by the National Metrology Institute of Japan (NMIJ) and coded as NMIJ CRM 7204-a, in which the concentrations of trace elements were elevated to facilitate the quality control in analysis for environment conservation purpose. It is a complement to CRMs aimed at quality control in natural seawater samples, e.g. NASS and CASS series by National Research Council of Canada, as well as GEOTRACES standards and reference materials. NMIJ CRM 7204-a was characterized for the analysis of 10 regulated trace elements (Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Cd, and Pb) and provided in 500 mL polyethylene bottle. Homogeneity test and stability study on the elements were carried out by inductively coupled plasma tandem quadrupole mass spectrometry. A property value was calculated as the weighted mean of the results obtained by multiple methods, whose weights were obtained as the reciprocal of their standard uncertainties. Combined uncertainty of a property value was the root mean square of the standard uncertainties of homogeneity, stability, analysis reproducibility, method-to-method variance, and calibrating standard. The concentration of Cd in NMIJ CRM 7204-a is approximately 3 µg/kg, while those of other trace elements are around 10 µg/kg. The concentrations of Na, Mg, K, and Ca were provided as information values, along with the density values at 15, 20, and 25° Celsius.

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)0.005
metaresearch head score (Gemma)0.006
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: Methods · Consensus signal: Methods
Teacher disagreement score0.014
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0040.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0100.009

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 head0.035
GPT teacher head0.274
Teacher spread0.239 · 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
GenreMethods

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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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