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Record W2167550816 · doi:10.1109/icvc.1999.820881

Investigations in polysilicon CMP to apply in sub-quarter micron DRAM device

2003· article· en· W2167550816 on OpenAlexaboutno aff
Jeong Deog Koh, D. W. Suh, Dong Won Han, Jin Woong Kim, Nae Hak Park, Sang Beom Han

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsnot available
Fundersnot available
KeywordsDramQuarter (Canadian coin)Random access memoryElectrical engineeringComputer scienceOptoelectronicsMaterials scienceEngineeringComputer hardware

Abstract

fetched live from OpenAlex

The chemical mechanical polishing (CMP) of polysilicon is an important technique to form polysilicon plugs or damascene lines in a sub-quarter micron DRAM device. The removal of polysilicon by CMP can reduced the recess in polysilicon plugs compared with conventional reactive ion etch (RIE). Furthermore, the damascene line scheme of polysilicon prevents serious voids formation and significant amounts of recess in inter layer dielectric (ILD) before formation of the contact. We discuss the characteristics of polysilicon CMP and the post cleaning process. In this paper, we also compared the performance of the polysilicon plug with that of the polysilicon damascene line by CMP.

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 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 score0.026
Threshold uncertainty score0.445

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 head0.011
GPT teacher head0.212
Teacher spread0.202 · 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.

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

Citations3
Published2003
Admission routes1
Has abstractyes

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