Acceleration and Extension of Opportunity Recognition for Nanotechnologies and Other Emerging Technologies
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.
Bibliographic record
Abstract
Commercialization and transfer of technology from laboratories in academe, government, and industry has only met a fraction of its potential. Many suggest that the processes used are currently more of an art than a science. Here we provide a plausible normative model that is used for idea generation and opportunity recognition developed for and used at Sandia National Laboratories.The resultant `research value-added' process integrates technology description, the dual process model of innovation and a product introduction model.The model and process are presented as is the application of the model to technology developments from a research laboratory that are either potentially disruptive or sustaining.The generalizability of research value-added process to both disruptive and sustaining technologies is key to the success of the model and process. Consequently, it is of value in considering alternative uses for existing products, such as simulation software, or applications or research findings that are disruptive and or emerging technologies, such as nanotechnologies.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it