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Record W4392264694 · doi:10.1520/mnl722012fm

Front Matter

2013· paratext· en· W4392264694 on OpenAlexaff
Edmund W. White, Rey G. Montemayor

Bibliographic record

Venuenot available
Typeparatext
Languageen
FieldEngineering
TopicLubricants and Their Additives
Canadian institutionsImperial Oil (Canada)
Fundersnot available
KeywordsFront (military)GeologyOceanography

Abstract

fetched live from OpenAlex

This manual is sponsored by the Flammability Section of ASTM Subcommittee D02.08 of ASTM Committee D02 on Petroleum Products and Lubricants. Ed White volunteered to write the manual and with the help, advice, and input of a Technical Advisory and Resource Group (TARG), comprised of individuals knowledgeable in flash point determination. TARG consisted of Bud Nesvig, Michael Collier, Michael Sherratt, Susan Litka, Didier Pigeon, Roland Ashauer, Katsuhiko Shimodaira, Thomas Herold, Volkmar Wierzbicki, Len Wachel, Michael Palmer, Alex Lau, and Rey Monte-mayor. Sincere acknowledgment and gratitude are due to these individuals for making possible the publication of this manual.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.064
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0060.004
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.9360.937

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 head0.006
GPT teacher head0.192
Teacher spread0.186 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2013
Admission routes1
Has abstractyes

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