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Development of the measurement procedure and certified reference material of water mass fraction in a mineral oil

2021· article· en· W3206166587 on OpenAlexaboutno aff
М. Yu. Medvedevskikh, А. С. Сергеева, Yu. A. Karpov

Bibliographic record

VenueIndustrial laboratory Diagnostics of materials · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Measurement and Uncertainty Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsMass fractionFraction (chemistry)Certified reference materialsMineral waterMineral oilCoulometryMass spectrometryChemistryAnalytical Chemistry (journal)Process engineeringEnvironmental scienceChromatographyMaterials scienceMetallurgyDetection limitEngineering

Abstract

fetched live from OpenAlex

The necessity of developing certified reference materials (CRM) for the composition of mineral oil with a certified value of the mass fraction of water, traceable to the State Primary Standard of units of mass fraction and mass (molar) concentration of water in solid and liquid substances and materials GET 173–2017 is revealed proceeding from the review of standardized methods for determining the quality of mineral oils and approved types of reference materials (CRMs). Mineral hydraulic oil MIL-H-5606 of CONOSTAN series manufactured by SCP SCIENCE (Canada) was chosen as the CRM material to control the accuracy of the results of water determination in mineral oils using IR spectrometers. A procedure for reproducing the mass fraction of water in a mineral oil using a standard installation based on coulometric titration according to Karl Fischer method from the composition of GET 173–2017 has been developed. The relative expanded uncertainty (atk= 2) of measurement results of the water mass fraction in mineral oil is 7.1%. The requirements to the metrological characteristics of CRM were formulated: the interval of permissible certified values, the limits of the permissible values of the absolute error atP= 0.95, and the permissible value of the absolute expanded uncertainty atk= 2. The choice of the method of packaging and conditions of CRM storage were analyzed. Taking into account the consistency of the measurement results of the water mass fraction obtained by coulometric titration according to Karl Fischer method and using a Fluid Scan infrared spectrometer manufactured by Spectro Inc., USA, the applicability of CRMs for metrological support of express IR spectrometers was demonstrated.

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)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.293
GPT teacher head0.346
Teacher spread0.054 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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