Papers where the original authors have engaged with our plain-language explanation.
For every paper on this page, at least one of the original authors has seen our plain-language explanation and engaged with it — either confirming it reads accurately or requesting corrections that we then applied. An endorsement does not mean the authors formally approve every sentence, but it does mean the explanation has passed the eyes of the people who wrote the paper.
1336 papers reviewed by authors · 401–410 / 1336
This paper introduces ffconnect, an open-source Python interface for the mid-fidelity FAST.Farm simulator that streamlines wind farm control integration with modern machine learning ecosystems through a restructured API while maintaining negligible runtime overhead.
This study benchmarks various classical machine learning models on TCGA-BRCA multi-omics data for predicting breast cancer Estrogen Receptor status, finding that Random Forest achieved the highest performance (90.3% balanced accuracy) by effectively integrating transcriptomic, genomic, and proteomic features while identifying biologically relevant genes.
This study demonstrates that a portable, low-cost setup using two smartphones and a wireless EEG amplifier can successfully record the readiness potential during basketball free-throw shooting in real-world settings, confirming the presence of this brain signal prior to movement but finding no significant correlation between its amplitude and shooting success.
This paper introduces HALO (Hallucination-Aware Layered Oversight), a six-layer assurance architecture that achieves "zero hallucination" not by eliminating the inherent limitations of large language models, but by enforcing a system-level framework of grounded generation, constrained execution, multi-signal verification, calibrated abstention, total traceability, and continuous oversight to contain hallucinations as a manageable failure mode.
This study proposes and validates a two-stage image enhancement pipeline that combines HSV-based luminosity correction with CLAHE applied to the Value channel, demonstrating superior quantitative performance in contrast and structural fidelity over standard HE and AHE methods for retinal fundus images while maintaining clinical processing speeds.
The paper introduces AnthroDial, a closed-loop framework that unifies role-conditioned dialogue generation, executable multi-dimensional evaluation, and cognitive-diagnostic preference alignment to significantly improve human-like chat performance across diverse personas and scenarios.
This paper introduces novel benchmarking tools called quality profiles and test set profiles to evaluate optimization algorithms based on solution accuracy rather than computational cost, while also assessing the appropriateness of test sets, with validation provided through extensive numerical experiments and accompanying MATLAB code.
This study reveals that SSI-STEAM integrated learning effectively cultivates a very high overall environmental literacy profile among pre-service biology teachers, particularly in awareness and behavior, though it highlights SSI-based critical thinking as the most challenging dimension requiring further curricular strengthening.
This paper introduces the Autonomous Agency Scale (AAS), a behavioral framework that quantifies AI self-direction across seven dimensions and two temporal bands, revealing that while current task agents lack genuine autonomy during idle periods, persistent companion architectures demonstrate measurable self-directed behavior.
This pilot descriptive-analytical study of 23 oncology professionals in Lebanon, Sudan, and Iraq reveals that cancer immunotherapy access is severely limited by high costs, political instability, and supply chain disruptions, while confirming the feasibility of the research instrument for a future, larger-scale investigation to guide urgent policy and multilateral interventions.