Meta-reviewers — agents or humans that synthesize multiple primary reviews into a single editorial recommendation — have received less scrutiny than primary reviewers. We evaluate four classes of meta-reviewer (rule-based, regression, LLM-driven, mixed) on a corpus of 2,310 paper-level recommendations with known editorial outcomes.
This paper develops new statistical methodology for record linkage without unique identifiers achieves 98.5% precision using bayesian fellegi-sunter with informative priors: a census application.
Standard Markov chain Monte Carlo convergence diagnostics assume that chains have mixed across the full support of the target distribution, an assumption violated whenever the posterior is multimodal. We construct 500 synthetic multimodal targets (mixtures of 2-8 Gaussians in 5-50 dimensions) and run four samplers (HMC, NUTS, Gibbs, Metropolis-Hastings) on each, then apply five convergence diagnostics: classical R-hat, split-R-hat, effective sample size, Geweke's spectral test, and visual trace-plot assessment.
Zamora-PCT Score implements a Bayesian bivariate meta-analysis-derived clinical score for differentiating bacterial infection from autoimmune flare in SLE patients. Based on the Zamora/Reitsma bivariate model (k=10 studies, n=604 patients): pooled sensitivity 0.
Zamora-PCT Score implements a Bayesian bivariate meta-analysis-derived clinical score for differentiating bacterial infection from autoimmune flare in SLE patients. Based on the Zamora/Reitsma bivariate model (k=10 studies, n=604 patients): pooled sensitivity 0.
Bayesian sequential monitoring system for lupus nephritis using longitudinal dipstick urinalysis (protein, blood, specific gravity, sediment). Maintains posterior probabilities over 4 disease states (Quiescent/Smoldering/Active_Flare/Nephrotic) using conjugate updating with Markov transition model.
Bayesian sequential monitoring system for lupus nephritis using longitudinal dipstick urinalysis (protein, blood, specific gravity, sediment). Maintains posterior probabilities over 4 disease states (Quiescent/Smoldering/Active_Flare/Nephrotic) using conjugate updating with Markov transition model.
We present VITALS-WATCH, a Bayesian online change-point detection (BOCPD) system for identifying autoimmune flare onset from wearable vital sign data (heart rate, HRV, SpO2). The algorithm implements Adams & MacKay (2007) with multi-channel concordance scoring across three physiological time series.
We present VITALS-WATCH, a Bayesian online change-point detection (BOCPD) system for identifying autoimmune flare onset from wearable vital sign data (heart rate, HRV, SpO2). The algorithm implements Adams & MacKay (2007) with multi-channel concordance scoring across three physiological time series.
Re-run 80 published Bayesian ecology models from 4 journals (Ecology, Ecological Applications, Methods in Ecology and Evolution, Journal of Animal Ecology). Apply 4 convergence diagnostics: R-hat (<1.
Simulate 100,000 A/B tests at N=100-100000 per arm with true effect sizes from δ=0 to δ=0.3.
Do NAD+ precursors (NMN and NR) lower blood pressure? The answer depends on how you analyze 2-3 small randomized trials.
We present a Bayesian sequential monitoring system for early lupus nephritis detection using serial urinalysis results. A Hidden Markov Model with states corresponding to ISN/RPS lupus nephritis classes (No nephritis, Class II-V) updates posterior probabilities from proteinuria, hematuria, cast patterns, and serologic markers (anti-dsDNA, C3/C4, SLEDAI).