Hugo Gonzalez Velozo

Peer review serves as the cornerstone of scientific quality control. Yet, the current journal-centric system is hindered by long timelines, high publication costs, inconsistent review quality, systemic biases, and editorial gatekeeping. Notably, the system relies on misaligned measures of impact that are tethered to journal branding and conflate scientific rigor ( Quality ) with perceived significance ( Impact ). Here, we report findings from the Discovery Stack Pilot Study, which tested a scientist-designed, journal-independent peer review model. The Discovery Stack model integrates in-line reviewer comments to promote constructive feedback and separately evaluates scientific Quality and Impact using defined criteria. To examine feasibility and effectiveness, manuscripts were reviewed in parallel with traditional journal review. A total of 162 reviews were completed, and survey data from 86 participants were analyzed. The results showed that reviewers effectively evaluated Quality and Impact as separate dimensions, with Quality scores being more consistent across reviewers than Impact scores. Participants strongly supported the core elements of the Discovery Stack model and expressed enthusiasm for its broader adoption to enhance transparency, efficiency, and value in peer review. Future studies will explore integrating this model into a digital platform for reviewing and curating scientific discoveries to improve the production and dissemination of high-quality research.

CD45 and CD69 are induced during 4T1 and MDA-MB-231 metastasis in mice

CD45 and CD69 surface protein after paclitaxel treatment in a subset of breast cancer cell lines

Clusters of cells expressing mammary keratins and identification of mammary epithelial cells in reduction mammoplasty samples from the Pal and colleagues and Kumar and colleagues scRNA-seq datasets

Continued experimental validation of neoplastic immune mimicry in breast cancer cell lines

Extended data for MDA-MB-231 CD69 CRISPR-activation experiments and the disruption of CD69 using CRISPR/Cas9

Extended scRNA-seq analysis of mimicked cell states in the Pal and colleagues human breast tumor scRNA-seq dataset

Clusters of cells expressing mammary keratins and identification of the neoplastic compartment in the PANNTHR human breast tumor scRNA-seq dataset