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Record W4416879590 · doi:10.37665/wergopj33851

State of the Industry - Introduction to Harsh Environments (Coatings/ Potting)

2023· article· W4416879590 on OpenAlexaboutno aff
Jason Keeping

Bibliographic record

VenueOn-Demand Webinars · 2023
Typearticle
Language
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsElectronicsExcellenceProcess (computing)State (computer science)Presentation (obstetrics)Design for manufacturability

Abstract

fetched live from OpenAlex

ABSTRACT Technical Presentation: With the current exponential growth in the Electronification of technology into harsh environments (such as the Electric Vehicle and Green Energy) there are various materials and processes that can be utilized. This presentation will briefly highlight these materials (different classifications) as well as their advantages as well as their challenges. Bio Summary: Jason Keeping is the Global Process Subject Matter Expert for Ruggedized Electronics within the Global Technology and Operations team at Celestica. He holds a B.A.Sc in Electrical Engineering from the University of Ryerson, is a Six Sigma/Lean Professional and a licensed professional engineer. Jason has focused his career on assessing the manufacturability and capabilities of conformal coating, potting, underfill chemistries & their interactions, dispensing technologies/processes and on assembly-level cleaning for the past fifteen years. Jason is the recipient of several awards, including the 2016 SMTA Excellence in International Leadership Award, the Shingo prize for Celestica's site in Monterrey, Mexico in 2007, and has contributed to Celestica's Frost & Sullivan awards in 2005, 2009, 2012 & 2013. Jason is the co-chair of the IPC-HDBK-830 handbook; author for conformal coating chapter of the Printed Circuits Handbook and was featured in the cover of Circuits Assembly in May 2008 and is currently the chair of the 5-30 Cleaning and Coating Committee within IPC. About the presenter: Jason Keeping P. Eng. Staff Engineer, Manufacturing Process (Ruggedized Electronics Sector) Global Technology and Operations Celestica Inc., Toronto, Canada Most recently, Jason presented with Dave Hillman of Collins Aerospace; an industry wide baseline study, on conformal coating, supporting a J-STD-001 initiative with data and support of industry leading organizations. Jason has worked alongside Steph Mescheter of BAE Systems as a principle investigator on two of Celestica's joint U.S. DoD Strategic Environmental Research and Development Project (SERDP) examining corrosion induced whisker growth Files Available to Download: Recorded Presentation (On-Demand) Slides (PDF)

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.055
GPT teacher head0.233
Teacher spread0.178 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

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