MétaCan
Menu
Back to cohort
Record W3201782437 · doi:10.1016/j.measen.2021.100293

International development of the SI in FAIR digital data

2021· article· en· W3201782437 on OpenAlexaff
Stuart Chalk, Diego Nahuel Coppa, F. Flamenco, Alistair Forbes, B. D. Hall, R. J. Hanisch, Kazumoto Hosaka, Daniel Hutzschenreuter, J.S. Park, R. M. White

Bibliographic record

VenueMeasurement Sensors · 2021
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsTraceabilityTask (project management)Task groupComputer scienceDigital dataData scienceWorld Wide WebPolitical scienceEngineeringEngineering managementTelecommunicationsSoftware engineeringSystems engineering

Abstract

fetched live from OpenAlex

The International Committee for Weights and Measures has recognised the need to provide support for digital representations of the International System of Units (SI) and related metrological concepts, such as traceability and measurement uncertainty. A specialised Task Group was established to address this in 2019. This summary reports on the activities of the task group to date, which include an overarching “Grand Vision” document, sketching out an SI Digital Framework, and an international online workshop, “The SI in FAIR digital data”, held in February 2021, to engage a wide audience in discussions about a solution.

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)0.068
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.359

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0680.059
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.009
Science and technology studies0.0040.012
Scholarly communication0.0160.022
Open science0.0040.015
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0210.005

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 head0.262
GPT teacher head0.345
Teacher spread0.083 · 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.

Study designNot applicable
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

Citations14
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueMeasurement SensorsSame topicResearch Data Management PracticesFrench-language works237,207