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Record W2567672738 · doi:10.22215/timreview/1041

Collaborative Innovation with External Actors: An Empirical Study on Open Innovation Platforms in Smart Cities

2016· article· en· W2567672738 on OpenAlexvenueno aff
Jukka Ojasalo, Heini Kauppinen

Bibliographic record

VenueTechnology Innovation Management Review · 2016
Typearticle
Languageen
FieldEngineering
TopicSmart Cities and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsInnovatorBusinessOpen innovationKnowledge managementMarketingSmart cityInternet of ThingsComputer scienceComputer securityEntrepreneurship

Abstract

fetched live from OpenAlex

IntroductionThe role of the cities is expanding from the producer and buyer of services into an innovator of services. Increasingly, cities need to initiate, foster, and enable innovation that offers solutions to their needs and problems (Bakici et al., 2013). Urban innovation is at the heart of the concept of a smart city (Caragliu et al., 2011; Hollands, 2008; Komninos,

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)0.010
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0030.003
Scholarly communication0.0050.006
Open science0.0010.004
Research integrity0.0020.002
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 head0.041
GPT teacher head0.325
Teacher spread0.285 · 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 designObservational
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

Citations57
Published2016
Admission routes1
Has abstractyes

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