A Perspective on Blockchain Smart Contracts: Reducing Uncertainty and Complexity in Value Exchange
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
The blockchain constitutes a technology-based, rather than social or regulation based, means to lower uncertainty about one another in order to exchange value. However, its use may very well also lead to increased complexity resulting from having to subsume work that displaced intermediary institutions had performed. We present our perspective that smart contracts may be used to mitigate this increased complexity. We further posit that smart contracts can be delineated according to complexity: Smart contracts that can be verified objectively without much uncertainty belong in an inter- organizational context; those that cannot be objectively verified belong in an intra- organizational context. We state that smart contracts that implement a formal (e.g. mathematical or simulation) model are especially beneficial for both contexts: They can be used to express and enforce inter-organizational agreements, and their basis in a common formalism may ensure effective evaluation and comparison between different intra-organizational contracts. Finally, we present a case study of our perspective by describing Intellichain, which implements formal, agent-based simulation model as a smart contract to provide epidemiological decision support.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| 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 it