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Record W2624381531 · doi:10.6028/nist.ir.6595

Materials reliability division, FY 2000 programs and accomplishments

2001· report· en· W2624381531 on OpenAlexaff
Fred R Fickett, Thomas A. Siewert

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsUniversity of Toronto
FundersNational Institute of Standards and Technology
KeywordsDivision (mathematics)Reliability (semiconductor)Reliability engineeringComputer scienceEngineeringMathematicsArithmeticPhysics

Abstract

fetched live from OpenAlex

The Materials Reliability Division develops measurement technologies that enable producers and users of materials to improve the quality and reliability of their products and to meet the ever more stringent materials challenges in the microelectronics market. The metrology devices and concepts, and the associated materials science base, cover the range of materials from metals to polymers to ceramics. Specimen dimensions range from the microscale and nanoscale of electronic packages and their components to the massive structures found in gas pipelines and bridges. Many measurement techniques are brought to bear on the problems, ranging from traditional and advanced ultrasonic testing to advanced transmission electron microscopy, scanned-probe microscopy, and new measurements yet to be named. The Division also provides measurements and standards to support the instruments necessary for assuring the accurate determination of impact resistance of structural steels through the standard reference materials (SRM) program. In FYOO the Division focused its resources on the following research areas:

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.858
Threshold uncertainty score1.000

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)0.0010.000

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 head0.022
GPT teacher head0.252
Teacher spread0.230 · 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 teacher head, 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

Citations0
Published2001
Admission routes1
Has abstractyes

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