Blockchain for Timely Transfer of Intellectual Property
Bibliographic record
Abstract
This article examines how blockchain technology can facilitate innovation by streamlining the licensing process of intellectual property (IP). In the traditional world, there can be tension between inventors and developers when it comes to licensing IP before a patent is granted. Developers need more information about the IP in order to estimate its value, while inventors are hesitant to disclose too much information for fear that developers will use it to develop and commercialize the IP without licensing it. The blockchain's ability to create a transparent and secure record of the inventing process can alleviate these concerns. On the one hand, blockchain's traceability helps protect IP from infringement, encouraging inventors to disclose more information about their high-value IP. On the other hand, developers have more incentive to license IP rather than infringe on it because of the risk of punishment. The size of the community maintaining the blockchain is a crucial factor in ensuring the validity of the blockchain. A community that is too large or too small would not be able to reach equilibrium. These findings provide insights into how blockchain can be used to improve the economics and marketing of IP.
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How this classification was reachedexpand
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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".