A screen can return hundreds of candidates. Effect size, guide support and technical artifacts all matter when choosing follow-up experiments.
SplicR ranks a screen's candidates by which survive contact with a second experiment. Across 124 held-out screen pairs, nine of its top ten reproduced in an independent screen, against seven for the screen's own effect size.
SplicR preserves method-specific statistics and reports their context and limitations. Independent validation-success probabilities are not available.
The research router did not improve on the published ensemble and was not promoted. Its paired uncertainty interval includes zero. These are retrospective ranking scores, not percentages of biological accuracy or independent validation.
Source: AssayBench test set, 334 screens published after 2021
The local engine checks inputs, runs applicable statistical methods and records evidence. Atlas entries retain their original methods; they are not uniformly reprocessed or calibrated.
Recorded effects, inspectable evidence and explicit uncertainty. Independent prospective validation remains outstanding.
This CHD1L row comes from the actual GSE145743 processed-count audit. It was not significant under the corrected q < 0.1 rule. No probability of successful validation has been assigned.
The earlier raw-read analysis used a different input and reported a different rank. It is retained in the research history and is not interchangeable with this result.
QC failed under the current dropout/depth criteria. Those criteria are not universal assay-quality standards. This single case does not establish validation precision.
Inspect methods, source and auditDiscuss a blinded evaluation with us. Predictions, outcome definitions and the analysis plan must be frozen before independent validation outcomes are revealed. This workflow still requires a laboratory partner.