<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>sulkysubject37.r-universe.dev</title><link>https://sulkysubject37.r-universe.dev</link><description>Recent package updates in sulkysubject37</description><generator>R-universe</generator><image><url>https://github.com/sulkysubject37.png</url><title>R packages by sulkysubject37</title><link>https://sulkysubject37.r-universe.dev</link></image><lastBuildDate>Fri, 06 Feb 2026 14:10:02 GMT</lastBuildDate><item><title>[sulkysubject37] resLIK 0.1.2</title><author>arshad10867c@gmail.com (MD. Arshad)</author><description>Implements the Representation-Level Control Surfaces
(RLCS) paradigm for ensuring the reliability of autonomous
systems and AI models. It provides three deterministic sensors:
Residual Likelihood (ResLik) for population-level anomaly
detection, Temporal Consistency Sensor (TCS) for drift and
shock detection, and Agreement Sensor for multi-modal
redundancy checks. These sensors feed into a standardized
control surface that issues 'PROCEED', 'DEFER', or 'ABSTAIN'
signals based on strict safety invariants, allowing systems to
detect and react to out-of-distribution states, sensor
failures, and environmental shifts before they propagate to
decision-making layers.</description><link>https://github.com/r-universe/sulkysubject37/actions/runs/25539943813</link><pubDate>Fri, 06 Feb 2026 14:10:02 GMT</pubDate><r:package>resLIK</r:package><r:version>0.1.2</r:version><r:status>success</r:status><r:repository>https://sulkysubject37.r-universe.dev</r:repository><r:upstream>https://github.com/cran/resLIK</r:upstream><r:article><r:source>rlcs-end-to-end.Rmd</r:source><r:filename>rlcs-end-to-end.html</r:filename><r:title>End-to-End RLCS Demonstration</r:title><r:created>2026-02-06 14:10:02</r:created><r:modified>2026-02-06 14:10:02</r:modified></r:article><r:article><r:source>rlcs-introduction.Rmd</r:source><r:filename>rlcs-introduction.html</r:filename><r:title>Introduction to RLCS</r:title><r:created>2026-02-06 14:10:02</r:created><r:modified>2026-02-06 14:10:02</r:modified></r:article></item><item><title>[sulkysubject37] annotaR 0.1.1</title><author>arshad10867c@gmail.com (MD. Arshad)</author><description>A framework for intuitive, multi-source gene and protein
annotation, with a focus on integrating functional genomics
with disease and drug data for translational insights. Methods
used include g:Profiler (Raudvere et al. (2019)
&lt;doi:10.1093/nar/gkz369&gt;), biomaRt (Durinck et al. (2009)
&lt;doi:10.1038/nprot.2009.97&gt;), and the Open Targets Platform
(Koscielny et al. (2017) &lt;doi:10.1093/nar/gkw1055&gt;).</description><link>https://github.com/r-universe/sulkysubject37/actions/runs/26563445406</link><pubDate>Thu, 22 Jan 2026 10:05:21 GMT</pubDate><r:package>annotaR</r:package><r:version>0.1.1</r:version><r:status>failure</r:status><r:repository>https://sulkysubject37.r-universe.dev</r:repository><r:upstream>https://github.com/sulkysubject37/annotar</r:upstream></item><item><title>[sulkysubject37] BioMoR 0.1.0</title><author>arshad10867c@gmail.com (MD. Arshad)</author><description>Provides tools for bioinformatics modeling using recursive
transformer-inspired architectures, autoencoders, random
forests, XGBoost, and stacked ensemble models. Includes
utilities for cross-validation, calibration, benchmarking, and
threshold optimization in predictive modeling workflows.</description><link>https://github.com/r-universe/sulkysubject37/actions/runs/25851245441</link><pubDate>Sun, 14 Dec 2025 09:14:13 GMT</pubDate><r:package>BioMoR</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://sulkysubject37.r-universe.dev</r:repository><r:upstream>https://github.com/sulkysubject37/biomor</r:upstream><r:article><r:source>biomor-autoencoder.Rmd</r:source><r:filename>biomor-autoencoder.html</r:filename><r:title>BioMoR Autoencoder</r:title><r:created>2025-09-21 09:20:09</r:created><r:modified>2025-09-21 09:20:09</r:modified></r:article><r:article><r:source>biomor-benchmarking.Rmd</r:source><r:filename>biomor-benchmarking.html</r:filename><r:title>BioMoR Benchmarking</r:title><r:created>2025-09-21 09:20:09</r:created><r:modified>2025-09-21 09:20:09</r:modified></r:article><r:article><r:source>biomor-intro.Rmd</r:source><r:filename>biomor-intro.html</r:filename><r:title>Introduction to BioMoR</r:title><r:created>2025-09-21 09:20:09</r:created><r:modified>2025-09-21 09:20:09</r:modified></r:article></item></channel></rss>