Here is how PCI is elevating the standards for open and reproducible science: introducing 4 already-existing and 2 new features 
#OpenScience #Reproducibility
1) Prioritizing robustness
Beyond recommender’s interest in the preprint, the primary criterion for a study's recommendation by PCI is its soundness. PCI supports preregistration through PCI Registered Reports and values high-quality replications equally with novel findings.
2) Full methodological disclosure
PCI demands complete descriptions of experimental procedures, ensuring peers can replicate the work from start to finish.
3) Open data as the default
Authors must deposit raw data + metadata allowing its reuse in a public repository that provides DOIs (e.g., Zenodo, Dryad) —no “available on request.”!
4) Open scripts and code
The same goes for statistical scripts, pipelines, and simulation code, which must be deposited in a versioned archive with a permanent ID (DOI or Software Heritage).
5) NEW: Reproducibility checks
To ensure shared data + code can reproduce all figures and numbers in manuscripts, PCI Ecology and PCI Evol Biol (other PCIs to join soon) invite data editors (thanks to https://ecoevo.social/@sortee members!) to verify data accessibility and computational reproducibility.
6) NEW: Justified study design
Empirical papers must now justify sample size via e.g., power analysis, Bayes thresholds, precision goals (quant) or saturation criteria (qual). Solid stats, fewer false negative and fewer false positives.
These new features (reproducibility checks and sample size justification), of course, only apply to new submissions
Mandatory open data + code, rigorous justification, transparent methods, and a culture of prereg & replication: this is how PCI contributes to making research more reproducible! For more information, see our author guidelines (https://buff.ly/JKZsyim). Feel free to share this thread and spread the word!