Analysis of the opportunities to implement the BIZ-TRIZ mechanism
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
Abstract Aiming to strengthen cooperation between scientific entities and enterprises and to overcome related obstacles, the authors propose to create a mechanism of incentives called BIZ-TRIZ, which is an abbreviation for “TRIZ for Business”. This mechanism is used to support cooperation between scientific entities and companies. Close cooperation is achieved by implementing R&D&I services, which is the responsibility of the scientific unit operating for the benefit of the companies involved. Research services are used together with the scientific instrument that reflects achievements in the modern theory of innovative problem solving (TRIZ). The analysis was made using the Maritime University of Szczecin and SME-type companies as an example. This paper describes the basic assumptions concerning the implementation of the BIZ-TRIZ mechanism. Also, it presents the use of SWOT analysis, needs/stakeholder analysis and risk analysis for the implementation of the BIZ-TRIZ mechanism. The paper describes preventative actions for the most important implementation risks and discusses the results of the analyses. Finally, it introduces the main conclusions regarding the purpose of implementing the BIZ-TRIZ mechanism.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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