MétaCan
Menu
Back to cohort
Record W1609761797 · doi:10.1063/1.1766734

Warpage Analysis of Silicon Wafer in Ingot Slicing by Wire-Saw Machine

2004· article· en· W1609761797 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAIP conference proceedings · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced Surface Polishing Techniques
Canadian institutionsCybernet Systems Corporation (Canada)
Fundersnot available
KeywordsSlicingIngotWaferImage warpingFinite element methodMaterials scienceSiliconMechanical engineeringEngineering drawingComputer scienceStructural engineeringEngineeringComposite materialMetallurgyOptoelectronics

Abstract

fetched live from OpenAlex

It is possible thermal expansion from heat generation by slicing deforms a single‐crystal silicon ingot but the authors can find no report on the point. In addition, numerical analysis is useful to clarify the mechanism of wafer warping but no paper has been reported the numerical analysis from the start to end of the wafer slicing process. The authors carried out experiments for the wafer slicing. In addition, a finite element analysis was carried out in order to solve the warping mechanism from the start to end of the wafer slicing process. The warp of wafer in the vertical direction was 6.05 μ m in the experiment whereas the warp in the finite element analysis was 5.30 μ m. The result by the finite element analysis gave good agreement with experimental one. This paper suggests that thermal expansion of the ingot has great influence on the warp of wafer.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.325
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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