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New Roadmap for Microelectronics: Charting the Semiconductor Industry's Path Over the Next 5, 10, and 20 Years

2024· article· en· W4408324946 on OpenAlexaff
Gamal Refai-Ahmed, V.V. Zhirnov, SB Park, Amr S. Helmy, Bahgat Sammakia, Kanad Ghose, James Ang, Griselda Bonilla, Tayseer Mahdi, Jim Wieser, Suresh Ramalingam

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Semiconductor Devices and Circuit Design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicroelectronicsSemiconductor industryPath (computing)Technology roadmapEngineeringManufacturing engineeringComputer scienceTelecommunicationsEngineering physicsElectrical engineeringBusinessMarketingComputer network

Abstract

fetched live from OpenAlex

In the past, the role of strategic planning for semiconductor industry was met by the international technology roadmap for semiconductors (ITRS), serving as a guiding light that provided manufacturers, designers, equipment suppliers, and researchers with direction years in advance. By providing a common framework for coordination across semiconductor industry stakeholder and, technology development efforts were efficient and aligned. However, the dissolution of the ITRS in 2015 left a void, leading to years of disconnected efforts. Recognizing the need for unified guidance, the industry rallied for the creation of a new strategic plan - the microelectronics and advanced packaging technologies (MAPT) roadmap (2023) that was developed through the synergistic efforts of industry, academic and government experts. This comprehensive plan outlines ambitious goals for the industry's future.

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)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.029
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0030.002
Scholarly communication0.0100.008
Open science0.0020.006
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0190.009

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 head0.024
GPT teacher head0.254
Teacher spread0.230 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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