MétaCan
Menu
Back to cohort

The Measurement of Residual Deformation in PBGA Package after Reflow Process Using A Newly Developed Laser Profiler

2006· article· en· W2007547152 on OpenAlexaff
Il‐Ho Kim, Ji Yoon, Soon Bok Lee

Bibliographic record

VenueKey engineering materials · 2006
Typearticle
Languageen
FieldEngineering
TopicIndustrial Vision Systems and Defect Detection
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsMaterials scienceScannerDeformation (meteorology)LaserResidualLaser scanningProcess (computing)Displacement (psychology)OpticsComputer scienceComposite material

Abstract

fetched live from OpenAlex

For measuring deformation of electronic packages, various techniques have been used. Each technique has some merits and demerits. Some techniques have very high resolution but small measuring area. On the contrary, other techniques have large measuring area and low resolution. So the judicious selection of techniques with a trade-off between the resolution and available measuring area is important. In this research, a new laser profiler was developed by integrating high resolution laser displacement sensor into the x-y scanner. This system has 10nm vertical resolution and 100nm horizontal resolution with a measurement area up to 25mm by 25mm. The residual deformation of a lead-contained and lead-free PBGA package after reflow process was measured by the newly developed system. And the effect of aging was evaluated.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.019
GPT teacher head0.220
Teacher spread0.201 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueKey engineering materialsSame topicIndustrial Vision Systems and Defect DetectionFrench-language works237,207