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Record W3094545710 · doi:10.1080/23311916.2020.1829805

Industry and academia partnership for aquatic renewable energy development in Colombia: A knowledge-education transfer model from the United Kingdom to Colombia

2020· article· en· W3094545710 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCogent Engineering · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicUniversity-Industry-Government Innovation Models
Canadian institutionsOlds College
Fundersnot available
KeywordsGeneral partnershipContext (archaeology)StakeholderCurriculumKnowledge transferTeamworkRenewable energyKnowledge managementBusinessEngineeringPolitical sciencePublic relationsSociologyManagementComputer scienceGeographyPedagogyEconomics

Abstract

fetched live from OpenAlex

The need for “industry-academia knowledge transfer (IAKT)” and close collaboration in Colombia has been recognised as critical to innovation, while in the United Kingdom (UK) an IAKT model has been successfully deployed in the UK benefitting both stakeholders. As a result in Colombia, an IAKT model does not exist to guide these two key stakeholder groups. The methodology used is based on the analysis of the data collected directly from the aquatic renewable energy (ARE) industry and academia in the Orkney islands (Scotland). In addition, literature available in the public domain was used and analysed. Having this information, a knowledge-education model is proposed for the Colombian context. The IAKT model curriculum was based on ARE course topics and validated in a preliminary phase with UCC undergraduate engineering students from different disciplines. The results were very promising in terms of the skills developed by the students, not only technical but also in communication skills, teamwork, critical thinking and so on.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.757

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.068
GPT teacher head0.244
Teacher spread0.176 · 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