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Record W3160804957 · doi:10.1007/s12594-020-1544-7

Role of Energy Dispersive XRF (ED-XRF) in Development of Rare Earth Element-2, International Certified Standard Reference Material: Ambiguities and Constraints

2020· article· en· W3160804957 on OpenAlexaboutno aff
P. V. Sunder Raju

Bibliographic record

VenueJournal of the Geological Society of India · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Measurement and Uncertainty Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsRare-earth elementCertified reference materialsGeologyRare earthCertificationNISTMineralogyGeochemistryEarth scienceGeophysicsComputer scienceStatisticsPolitical scienceMathematicsNatural language processingLaw

Abstract

fetched live from OpenAlex

Abstract The REE-2 is a carbonatite sample with rare earth elements provided from a Canadian mining company and distributed by Canadian Certified Reference Materials (CCRM), Canada. The reference material was provided to participate in the testing process (round-robin) and CSIR-NGRI, Hyderabad, state of the art analytical technique Energy Dispersive X-ray fluorescence (EDXRF) also contributed to the development of this (REE −2) reference material. In this paper, the efficacy of analytical protocol developed and comparing the results with twenty one industrial, commercial and government laboratories across globe in an inter-laboratory measurement program are presented. The CSIR-NGRI, EDXRF analytical facility contribution and steps to overcome during REE-2 development are briefly discussed. This contribution is to highlight the international analytical standards and protocols maintained at EDXRF laboratory vis-à-vis international laboratories.

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)0.035
metaresearch head score (Gemma)0.030
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.134
GPT teacher head0.327
Teacher spread0.193 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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