KWELA: Hierarchical Adaptive 'RT-QuIC' Classification for Complex
Matrices
Extends 'RT-QuIC' (Real-Time Quaking-Induced Conversion) statistical
analysis to complex environmental matrices through hierarchical adaptive
classification. 'KWELA' is named after a deity of the Fore people of Papua
New Guinea, among whom Kuru, a notable human prion disease, was identified.
Implements a 6-layer architecture: hard gate biological constraints,
per-well adaptive scoring, separation-aware combination, Youden-optimized
cutoffs, replicate consensus, and matrix instability detection. Features
dual-mode operation (diagnostic/research), auto-profile selection
(Standard/Sensitive/Matrix-Robust), RAF integration for artifact detection,
matrix-aware baseline correction, and multiple consensus rules. Methods
include energy distance (Szekely and Rizzo (2013) <doi:10.1016/j.jspi.2013.03.018>),
CRPS (Gneiting and Raftery (2007) <doi:10.1198/016214506000001437>),
SSMD (Zhang (2007) <doi:10.1016/j.ygeno.2007.01.005>),
and Jensen-Shannon divergence (Lin (1991) <doi:10.1109/18.61115>). This
package implements methodology currently under peer review; please contact
the author before publication using this approach. Development followed an
iterative human-machine collaboration where all algorithmic design,
statistical methodologies, and biological validation logic were
conceptualized, tested, and iteratively refined by Richard A. Feiss through
repeated cycles of running experimental data, evaluating analytical outputs,
and selecting among candidate algorithms and approaches. AI systems
('Anthropic Claude' and 'OpenAI GPT') served as coding assistants and
analytical sounding boards under continuous human direction. The selection
of statistical methods, evaluation of biological plausibility, and all final
methodology decisions were made by the human author. AI systems did not
independently originate algorithms, statistical approaches, or scientific
methodologies.
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=KWELA
to link to this page.
[aut, cre]