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Record W3108762009 · doi:10.1515/pac-2019-0302

Vocabulary of radioanalytical methods (IUPAC Recommendations 2020)

2020· article· en· W3108762009 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

VenuePure and Applied Chemistry · 2020
Typearticle
Languageen
FieldChemistry
TopicRadioactive element chemistry and processing
Canadian institutionsDalhousie University
FundersInternational Union of Pure and Applied Chemistry
KeywordsNuclideChemistryCharacterization (materials science)RadiochemistryNuclear physicsPhysics

Abstract

fetched live from OpenAlex

Abstract These recommendations are a vocabulary of basic radioanalytical terms which are relevant to radioanalysis, nuclear analysis and related techniques. Radioanalytical methods consider all nuclear-related techniques for the characterization of materials where ‘characterization’ refers to compositional (in terms of the identity and quantity of specified elements, nuclides, and their chemical species) and structural (in terms of location, dislocation, etc. of specified elements, nuclides, and their species) analyses, involving nuclear processes (nuclear reactions, nuclear radiations, etc. ), nuclear techniques (reactors, accelerators, radiation detectors, etc. ), and nuclear effects (hyperfine interactions, etc. ). In the present compilation, basic radioanalytical terms are included which are relevant to radioanalysis, nuclear analysis and related techniques.

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 categoriesInsufficient payload (model declined to judge)
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 score0.626
Threshold uncertainty score0.998

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)0.0030.000

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 head0.020
GPT teacher head0.313
Teacher spread0.293 · 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