MétaCan
Menu
Back to cohort
Record W2143570349 · doi:10.1109/ipfa.2009.5232667

High-temperature Conductive-AFM technique for resolution of soft failures

2009· article· en· W2143570349 on OpenAlex
Lim Soon Huat, Sun Wanxin, Vinod Narang, J.M. Chin

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIntegrated Circuits and Semiconductor Failure Analysis
Canadian institutionsAdvanced Micro Devices (Canada)
Fundersnot available
KeywordsMaterials scienceTransistorElectrical conductorStatic random-access memoryOptoelectronicsSilicon on insulatorLeakage (economics)Conductive atomic force microscopyInsulator (electricity)OxideNanotechnologySiliconElectrical engineeringAtomic force microscopyVoltageComposite materialEngineering

Abstract

fetched live from OpenAlex

This paper demonstrates the Veeco heating stage for high temperature Conductive-AFM analysis which is very useful for revealing leaky contacts associated with soft failures. CAFM at 80°C is performed on SOI transistors to isolate leaky polysilicon gate contacts. Nanoprobing at high temperature is performed and it shows strong correlation with the high temperature CAFM data. High temperature CAFM helped to isolate higher gate oxide leakage current in the failing transistor in SRAM memory cell.

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 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 score0.326
Threshold uncertainty score0.505

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)0.0000.000

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 head0.008
GPT teacher head0.211
Teacher spread0.204 · 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