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Record W2054930192 · doi:10.1109/epec.2014.20

Assessment of Disruptive Innovation in Emerging Energy Technologies

2014· article· en· W2054930192 on OpenAlexaff
F.P. Adams, Blair P. Bromley, Monique Moore

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicInnovation Diffusion and Forecasting
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsDisruptive innovationDisruptive technologyRenewable energyEmerging technologiesPhotovoltaic systemEnergy technologyComputer scienceRisk analysis (engineering)Technology developmentBusinessEnvironmental economicsMarketingEngineeringElectrical engineeringEconomicsManufacturing engineering

Abstract

fetched live from OpenAlex

The concept of "disruptive innovation" offers a basis for understanding the structure and dynamics of technology-driven markets, and how they respond to emerging technologies. The concept may also prove useful in assessing the relative prospects for research and development in related fields, such as nuclear, renewable or other energy technologies. A trial assessment was performed on the potential for innovations to disrupt energy markets. Consumer-level photovoltaic power in areas with high insolation was found to be the most potentially disruptive innovation in energy technology, possibly enabled by advances in electrochemical energy storage battery technology. Such findings could provide useful input to strategies for energy technology development. Quantitative measures of comparison are necessary, and gaps in technology coverage weaken the assessment. Formal methods to identify and assess innovations are being developed.

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)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.035
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.004
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.080
GPT teacher head0.405
Teacher spread0.325 · 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 designTheoretical or conceptual
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
Published2014
Admission routes1
Has abstractyes

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