ArticleInnovation (Cambridge (Mass.))2025
Decentralized knowledge assessment.
Article in Innovation (Cambridge (Mass.)), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The peer-review process, which serves as the quality-control mechanism of scientific knowledge production, has been criticized for its bias, unreliability, and inefficiency. Academic conferences and journals typically rely on a centralized mechanism for reviewer assignment and paper assessment. We argue that this centralization is a major factor contributing to the unreliability of the review process, leading to deficiencies in the current knowledge-assessment systems. To address this, we propose a novel decentralized model that democratizes peer review by shifting decision-making rights from centralized authorities to all scholars participating in a scholarly community. Our model includes a dual-rewarding incentive mechanism that motivates scholars to actively participate in peer review by recognizing both their effort and scientific contributions. This model transforms peer review from passive judgment to active collaboration. We simulated the model in conference settings and demonstrated its potential to revolutionize knowledge production and dissemination.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.