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Record W2168278945 · doi:10.7202/037508ar

The nanotechnology revolution in Barcelona: innovation & creativity by universities

2009· article· en· W2168278945 on OpenAlexvenueno aff
Esteve Juanola‐Feliu

Bibliographic record

VenueManagement international · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicUniversity-Industry-Government Innovation Models
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityIntersection (aeronautics)EngineeringNanotechnologyInvestment (military)Engineering ethicsBusinessPolitical scienceMaterials scienceTransport engineering

Abstract

fetched live from OpenAlex

This paper analyses the state of the art for nanotechnology in Barcelona, focussing on the scientific and economic challenges arising from nanotechnologies and the creative and innovative framework in Barcelona that could be used to meet them. Nanotechnology is an endless source of innovation and creativity at the intersection of medicine, biotechnology, engineering, physical sciences and information technology, and it is opening up new directions in R + D, knowledge management and technology transfer. Given the huge economic investment and cutting-edge research in the field of nanotechnology, a creatively managed and cooperation-based university industry is more in demand than ever before.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0040.010
Scholarly communication0.0210.007
Open science0.0010.006
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.016
GPT teacher head0.228
Teacher spread0.212 · 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.

Study designQualitative
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

Citations5
Published2009
Admission routes1
Has abstractyes

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