The Contribution of Information Engineering for Innovation Funding Source Obtainment
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
<p>Continued innovation in products, processes, services, technology and on the company management, is essential to maintaining and achieve more competitiveness in organizations. To execute innovation projects, many companies seek external financial resources through development agencies. Taking into consideration few theoretical approaches on this topic, the Information Engineering presents itself as an element that can contribute for this process. Therefore, this study aims to find out how the information engineering can support and improve the process of funds obtainment to innovation purposes in organizations. This is an exploratory study through a systematic literature review method, which addresses three main steps: planning, processing and divulgation. The results show that the ability to manage information has a positive and direct influence on the performance of organizational innovation. Therefore, it is possible to realize that as the more information is structured and implemented more are the chances of successful in the innovation processes including funding source obtainment.</p>
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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