Intellectual property strategies, collaboration and technological capabilities: The fuel cell cluster in Vancouver, BC
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
This paper describes the development of the fuel cell cluster in Vancouver, Canada, with data collected over three years. This allows to following up the links that come up and the patterns and purposes of collaboration among cluster actors. Knowledge flows through patenting and the university role on the knowledge creation are key issues for this research. Other factors considered are: access to venture capital, characteristics of the city where the cluster is located, and the policies oriented to support its development. The paper is organized in five parts: (i) The ways to collaborate and the links produced between different types of organizations. (ii) The role of customers, suppliers and competitors to produce innovations and the identification of fuel cells market opportunities. Particularly, the paper addresses the role of the university on the fuel cell market development because some differences related to the traditional role reported in the clusters literature were found. (iii) The geographic location of the cluster and the analysis of policies behind the cluster growth. (iv) The intellectual property strategies to protect knowledge and commercialize it at the fuel cell market. (v) The identification of core capabilities that have positioned companies as competitors on the international market
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 | 0.001 | 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