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Record W6925545902 · doi:10.17920/g9p89k

Novel green technologies for producing organic electronics

2009· other· en· W6925545902 on OpenAlexaboutno aff

Bibliographic record

VenueCalifornia Digital Library · 2009
Typeother
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)Wearable technologyWearable computerElectronicsPower consumptionConsumption (sociology)

Abstract

fetched live from OpenAlex

The long-term goal of the proposed Collaborative Events is to build an enterprise of green manufacturing of solution-based organic electronics. Combining their strengths, Canada and California could be the most powerful global players in the rapidly expanding market of organic electronics, which is expected to reach $300 billion per year by 2025. The solution-based manufacturing approach reduces costs and enables the practical fabrication of new consumer products such as roll-up displays for computers and cell phones, flexible solar panels for power portable equipment, low cost electronic labels, and flexible sensors for wearable health-care biotechnology products. The applicants (Lau of UWO in Canada and Graves of UC Berkeley in California) have relevant intellectual properties, technical experience, and the collaborative network to competitively develop innovative technologies to accomplish the goal of further increasing the throughput of production and reducing the consumption of energy and chemicals in solution-based production of organic electronics. To start this development, they will promote their novel value-chain approach of collaborative technology innovation, through their proposed CCSIP Collaborative Events, to the qualified academic and industrial researchers to find the best partners to work with them on adding more intellectual properties to the value chain of green production of organic electronics. Specifically, the proposed Collaborative Events comprise the following: (a) visit by Graves to UWO and four other research institutes for networking and information collection; (b) a workshop at UWO during the visit of Graves for him, Lau and other Canadian researchers to draft their collaboration strategy; (c) visit by Lau and his coworkers to Berkeley, UCSB and two companies in California for networking, information collection, and promotion of the relevant inventions of Lau; (d) a workshop at Berkeley during the visit of Lau for his team, Graves, and other researchers to enrich the collaboration strategy; and (e) one or two follow-up visits by Lau to California to firm up the academic and industrial partners in the follow-up value-chain collaboration. Through these events, the network is expected to expand from the partnership of UWO and Berkeley to the following potential institutional partners: Univ. of Windsor, McMaster Univ., Univ. of Toronto, Institute of Microstructural Sciences/NRC, Univ. of Quebec in Montreal, Rosstech Signals Inc. (Ontario), UCSB, Univ. of Washington, Lam Research Inc., and Applied Materials Inc. These confirmed and potential partners are all active in organic electronics. More than 200 researchers including students, researchers, and managers/administrators in these organizations will participate in the Collaborative Events, learn the novel value-chain approach of collaborative technology innovation, and plan their follow-up collaborative development of green production of organic electronics.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.192
Teacher spread0.184 · 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
Published2009
Admission routes1
Has abstractyes

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