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252 papers

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Stopping Is a Conditional Decision: Corpus Qualification, Bayesian Sequential Stopping, and the Limits of Early Termination in Scholarly Literature Screening

This paper proposes a two-stage framework separating corpus qualification from Bayesian sequential stopping to demonstrate that even well-calibrated models and improved ranking cannot guarantee safe early termination in scholarly literature screening, as evidenced by high premature-stop rates and low recall in benchmark validations.

Mohammad Pashaᵃ, Mohammed Ali Shaikᵇ2026-09-08
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Spatio-temporal modelling of provincial Human Development Index in Indonesia: a comparison of six forecasting approaches

This study evaluates six spatio-temporal models for forecasting Indonesia's provincial Human Development Index, finding that simple local and cluster-adjusted approaches outperform complex deep learning architectures in short-term predictions, particularly when accounting for administrative boundary changes and limited training data.

I Gusti Ngurah Sentana Putra, Muh Akbar Idris2026-09-08
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Global Benford Deviation Clustering (GBDC): A Spatial Framework for Unsupervised Radiometric Anomaly Detection in Multispectral Imagery

This paper introduces the Global Benford Deviation Clustering (GBDC) framework, a novel unsupervised method that transforms global Benford's Law deviations into per-pixel anomaly scores to enable training-free radiometric anomaly detection in multispectral imagery, achieving a baseline mean F1-score of 0.347 on the CloudSEN12 dataset.

Shaho Piroti, Parviz Zeaieanfirouzabadi, Saman Ghafari2026-09-08
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Beyond Pairwise Polarization: A Statistical Null Model for Structural Balance in Signed Hypergraphs

This paper introduces a statistically rigorous framework for testing structural balance in signed hypergraphs by defining a Hyperedge Frustration Index and a degree-preserving null model, which applied to UN General Assembly voting data reveals that genuine higher-order polarization exists only in specific historical windows rather than as a universal constant, distinguishing real coalitions from chance.

Md Hasibuzzaman, Chan-Yun Yang, Gene Eu Jan2026-09-07
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Conflict inherits the frame: bin geometry and BPA construction in evidential fusion of quantised continuous evidence

This paper demonstrates that in Dempster-Shafer evidential fusion of quantized continuous data, the geometry of the binning frame artificially confounds conflict measures with evidence position, leading to a proposed excess-conflict statistic to correct this bias while revealing that standard combination rules often reduce to Bayesian products with negligible efficacy differences in predicting software vulnerability exploitation.

Elena Udrescu, Alexandru Udrescu, Ana-Maria Suduc, Mihai Bîzoi2026-09-07
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From reference materials to examination results: a specification-anchored framework for version-defined qualitative properties

This paper proposes a specification-anchored framework that extends ISO 33406 to address version-dependent variability in complex molecular examinations by defining minimum reporting requirements, distinguishing analytical layers, and establishing falsifiable propositions to ensure the traceability and comparability of examination results.

Guigao Lin2026-09-07
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A Gaussian mixture model for discovering latent group structures in classification problems with multiple classes

This paper proposes a novel Grouped Gaussian Mixture Model (GGM) with an efficient Expectation-Maximization algorithm to discover interpretable latent group structures among multiple categories in a fully data-driven manner, demonstrating superior performance over existing methods in both simulations and e-commerce applications.

Hong Chang, Xuetong Li, Ke Xu, Hansheng Wang2026-09-07
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Evaluating missing-data workflows under hospital-structured missingness: a simulation-calibrated study in eICU and MIMIC-IV

This study demonstrates that hospital-structured missingness in multicenter electronic health records significantly biases mortality association estimates and undermines confidence interval coverage across conventional missing-data workflows, highlighting the critical need for cluster-level diagnostics, method-specific performance comparisons, and explicit missing-not-at-random sensitivity analyses.

Jiancheng Zhang, Jianying Dai, Qingjiang Lyu2026-09-04
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Network-Adjusted Empirical Bayes Estimation of Age-Specific Adult Mortality from DHS Sibling Survival Histories: Evidence from Nigeria

This paper introduces a network-adjusted empirical Bayes framework to correct visibility bias and sampling variability in Nigerian sibling survival histories, revealing that adult mortality declined between 2018 and 2024 and is significantly lower than previously estimated by conventional methods and international reference series.

Shorful Alam, Nazmul Haque, Abdul Mazed, Md. Sabbir Ahmed Mayen, Md. Abu Kowser, Mahadie Hassan2026-09-04