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Failure-mode index

Search what already failed

A searchable index of real negative results, null findings, and replication failures from the published literature — so you can learn what didn't work before repeating it.

WASTE indexes published research — it does not host or republish full papers. Each entry is a metadata record (title, authors, DOI) compiled from open scholarly databases, with the abstract shown in full only where the paper is openly licensed (e.g. Creative Commons); otherwise a short excerpt is shown for reference under fair use. WASTE classifies each work by failure type; classifications are automated and approximate.

741 results for "aging" · page 9 of 25

Negative / Null Result Report

CT Radiomics Models Did Not Outperform Experts in Predicting [68Ga]Ga-PSMA-PET Positivity in Prostate Cancer Lymph Node Staging

Thula Cannon Walter-Rittel, Boris Gorodetski, Alexander Hartenstein et al. · 2026 · Current Oncology

Background: The use of [68Ga]Ga-PSMA-PET/CT for prostate cancer (PCa) staging is limited by cost and availability. This study evaluates whether radiomic features from contrast-enhanced (CE) CT can predict PSMA-positive lymph nodes (LNs) as…

View details →DOI: 10.3390/curroncol33030146
Negative / Null Result Report

Inflation Management In The Eu: Does The Eurozone Outperform Non-Euro States?

Anna Prucnal · 2025 · International Journal of Business & Management Studies

This study examines the effectiveness of the monetary policy of the European Central Bank (ECB) in managing inflation in the Euro Area compared to the independent monetary policy of seven European Union Member States outside the Economic…

View details →DOI: 10.56734/ijbms.v6n1a7
Negative / Null Result Report

Downstream Imaging Studies Do Not Significantly Improve Outcome in Most Patients with Chest Pain Who Did Not Reach Their Target Heart Rate on a Stress ECHO Study

Nativ Henkin, Ifat Karilker, Sergio L. Kobal et al. · 2023 · Journal of Clinical Medicine

Echocardiographic stress tests are often used to evaluate patients who complain of chest pain. However, some patients fail to reach the target heart rate required for the test to be conclusive (usually defined as 85% of the predicted…

View details →DOI: 10.3390/jcm12144832
Negative / Null Result Report

Citrulline ingestion did not improve the age‐associated reduction in nitric oxide synthesis (698.6)

Il‐Young Kim, Scott Schutzler, Nicolaas Deutz et al. · 2014 · The FASEB Journal

A reduction in nitric oxide (NO) bioavailability that impairs peripheral blood flow regulation is a natural consequence of aging. Therefore , we investigated the effect of ingestion of citrulline, the precursor of arginine, on de novo…

View details →DOI: 10.1096/fasebj.28.1_supplement.698.6
Negative / Null Result Report

Double Stigma: The Influence of Race & Mental Health

Bobbie Call, null null, null null et al. · 2020 · John Heinrichs Scholarly & Creative Activities Day

Mental health stigma is prevalent and many people are affected all around the world (Watson, 2002). Stigma often prevents individuals with a mental illness from engaging in typical life routines (Corrigan, 2004). Individuals of ethnic…

View details →DOI: 10.58809/ccrp9120
Negative / Null Result ReportOpen accessMedicine

Functional MR Microimaging of Pancreatic β-Cell Activation

Barjor Gimi, Lara Leoni, Jose Oberholzer et al. · 2006 · Cell Transplantation

The increasing incidence of diabetes and the need to further understand its cellular basis has resulted in the development of new diagnostic and therapeutic techniques. Nonetheless, the quest to noninvasively ascertain β-cell mass and function has not been achieved. Manganese (Mn)-enhanced MRI is presented here as a tool to image β-cell functionality in cell culture and isolated islets. Similar to calcium, extracellular Mn was taken up by glucose-activated β-cells resulting in 200% increase in MRI contrast enhancement, versus nonactivated cells. Similarly, glucose-activated islets showed an in

View details →DOI: 10.3727/000000006783982151
Negative / Null Result Report

The Effects of Bisphenol A on Plant A

Michelle Storey, null null, null null et al. · 2020 · John Heinrichs Scholarly & Creative Activities Day

Bisphenol A (BPA) is a ubiquitous raw material used in the production of many everyday things such as food packaging and baby bottles. While there have been many studies about the effect that this can have on water and animals, there are…

View details →DOI: 10.58809/vacy9619
Negative / Null Result Report

Engaging Students in Distance Learning Discussions

Dorothy Ochs, null null, null null et al. · 2022 · John Heinrichs Scholarly & Creative Activities Day

Purpose: The purpose of this poster is to explore various types of discussion formats in order to find ones that keep the students thoughtfully engaged and motivated. • Methods: The poster will compare and contrast several different types…

View details →DOI: 10.58809/mkeu5488
Negative / Null Result ReportOpen accessComputer Science

Model-Agnostic AI Framework with Explicit Time Integration for Long-Term Fluid Dynamics Prediction

Sunwoong Yang, Ricardo Vinuesa, Namwoo Kang · 2024 · arXiv

This study addresses the critical challenge of error accumulation in spatio-temporal auto-regressive (AR) predictions within scientific machine learning models by exploring temporal integration schemes and adaptive multi-step rollout strategies. We introduce the first implementation of the two-step Adams-Bashforth method specifically tailored for data-driven AR prediction, leveraging historical derivative information to enhance numerical stability without additional computational overhead. To validate our approach, we systematically evaluate time integration schemes across canonical 2D PDEs be

Negative / Null Result ReportOpen accessDentistry

Dens invaginatus as a diagnostic challenge: evaluating large language models against expert endodontic reasoning

Damla Erkal, Turgut Felek, Oana-Paula Butean et al. · 2025 · BMC Oral Health

Abstract Introduction This study hypothesized that large language models (LLMs) would underperform compared to expert clinicians in diagnosing and managing complex endodontic anomalies, such as dens invaginatus, when provided with periapical radiographs. Although LLMs have shown promise in dental education and basic diagnostics, their effectiveness in nuanced clinical reasoning has remained unclear. Methods Nineteen anonymized periapical radiographs depicting challenging endodontic conditions were paired with clinical vignettes. Six advanced LLMs and one expert endodontist independently answer

View details →DOI: 10.1186/s12903-025-06987-z
Negative / Null Result ReportOpen accessComputer Science

WiFi-based Global Localization in Large-Scale Environments Leveraging Structural Priors from osmAG

Xu Ma, Jiajie Zhang, Fujing Xie et al. · 2025 · arXiv

Global localization is essential for autonomous robotics, especially in indoor environments where the GPS signal is denied. We propose a novel WiFi-based localization framework that leverages ubiquitous wireless infrastructure and the OpenStreetMap Area Graph (osmAG) for large-scale indoor environments. Our approach integrates signal propagation modeling with osmAG's geometric and topological priors. In the offline phase, an iterative optimization algorithm localizes WiFi Access Points (APs) by modeling wall attenuation, achieving a mean localization error of 3.79 m (35.3\% improvement over tr

Negative / Null Result Report

Comparison of insulin resistance and lipid profile in clinically significant macular oedema versus non-clinically significant macular oedema in patients with type 2 diabetes mellitus

· 2025 · International Journal of Medicine and Medical Research

Lifestyle-related disorders, particularly diabetes, pose a significant global health challenge. Diabetic macular oedema, a microvascular complication, highlights the importance of managing insulin resistance and hyperlipidaemia for optimal…

View details →DOI: 10.63341/ijmmr/1.2025.22
Negative / Null Result ReportOpen accessMedicine

The neural determinants of age-related changes in fluid intelligence: a pre-registered, longitudinal analysis in UK Biobank [version 1; referees: 2 approved]

Rogier A. Kievit, Delia Fuhrmann, Gesa Sophia Borgeest et al. · 2018 · Wellcome Open Research

Background: Fluid intelligence declines with advancing age, starting in early adulthood. Within-subject declines in fluid intelligence are highly correlated with contemporaneous declines in the ability to live and function independently. To support healthy aging, the mechanisms underlying these declines need to be better understood. Methods: In this pre-registered analysis, we applied latent growth curve modelling to investigate the neural determinants of longitudinal changes in fluid intelligence across three time points in 185,317 individuals (N=9,719 two waves, N=870 three waves) from the U

View details →DOI: 10.12688/wellcomeopenres.14241.1
Abandoned Hypothesis

Failed in aging? Queering in living with dementia

Valerie Keller · 2023 · Frontiers in Sociology

This article explored the ways in which living with dementia brings potentials to queer the concept of “successful aging” and associated notions of being human. Regarding the progressive development of dementia, it can be assumed that…

View details →DOI: 10.3389/fsoc.2023.1139271
Negative / Null Result Report

Assessing the Effect of Subsidy Removal on Cost- Significant Material and Labour within Anambra State Construction Economy

Uchechi Vanessa Alintah-Abel, Francisca Nkachukwu Okeke, Eucharia Chika Enebe · 2025 · British Journal of Multidisciplinary and Advanced Studies

The goal of most countries is the desire to maintain a stable price level of goods and services. This however, appears to be an uphill task given the incidence of subsidy removal that is presently ravaging the developing economies of the…

View details →DOI: 10.37745/bjmas.2022.04253
Negative / Null Result ReportOpen accessPhysics

Beyond the RPA on the cheap: improved correlation energies with the efficient "Radial Exchange Hole" kernel

Tim Gould · 2012 · arXiv

The "ACFD-RPA" correlation energy functional has been widely applied to a variety of systems to successfully predict energy differences, and less successfully predict absolute correlation energies. Here we present a parameter-free exchange-correlation kernel that systematically improves absolute correlation energies, while maintaining most of the good numerical properties that make the ACFD-RPA numerically tractable. The "RXH" kernel is constructed to approximate the true exchange kernel via a carefully weighted, easily computable radial averaging. Correlation energy errors of atoms with two t

Negative / Null Result ReportOpen accessComputer Science

On the Effectiveness of Mode Exploration in Bayesian Model Averaging for Neural Networks

John T. Holodnak, Allan B. Wollaber · 2021 · arXiv

Multiple techniques for producing calibrated predictive probabilities using deep neural networks in supervised learning settings have emerged that leverage approaches to ensemble diverse solutions discovered during cyclic training or training from multiple random starting points (deep ensembles). However, only a limited amount of work has investigated the utility of exploring the local region around each diverse solution (posterior mode). Using three well-known deep architectures on the CIFAR-10 dataset, we evaluate several simple methods for exploring local regions of the weight space with re

Negative / Null Result ReportOpen accessComputer Science

MedNet-PVS: A MedNeXt-Based Deep Learning Model for Automated Segmentation of Perivascular Spaces

Zhen Xuen Brandon Low, Rory Zhang, Hang Min et al. · 2025 · arXiv

Enlarged perivascular spaces (PVS) are increasingly recognized as biomarkers of cerebral small vessel disease, Alzheimer's disease, stroke, and aging-related neurodegeneration. However, manual segmentation of PVS is time-consuming and subject to moderate inter-rater reliability, while existing automated deep learning models have moderate performance and typically fail to generalize across diverse clinical and research MRI datasets. We adapted MedNeXt-L-k5, a Transformer-inspired 3D encoder-decoder convolutional network, for automated PVS segmentation. Two models were trained: one using a homog

Negative / Null Result ReportOpen accessEngineering

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

Arjun D. Desai, Francesco Caliva, Claudia Iriondo et al. · 2020 · arXiv

Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression. Methods: A dataset partition consisting of 3D knee MRI from 88 subjects at two timepoints with ground-truth articular (femoral, tibial, patellar) cartilage and meniscus segmentations was standardized. Challenge submissions and a majority-vote ensemble were evaluated using Dice score, average symmetric surface distance, volumetric overlap error, and coefficient of variation on a hold-out test set. Simil

Negative / Null Result ReportOpen accessComputer Science

Honey, I shrunk the scientist -- Evaluating 2D, 3D, and VR interfaces for navigating samples under the microscope

Jan Tiemann, Matthew McGinity, Ulrik Günther · 2026 · arXiv

In contemporary biology and medicine, 3D microscopy is one of the most widely-used techniques for imaging and manipulation of various kinds of samples. Navigating such a micrometer-sized, 3-dimensional sample under the microscope -- e.g. to find relevant imaging regions -- can pose a tedious challenge for the experimenter. In this paper, we examine whether 2D desktop, 3D desktop, or Virtual Reality (VR) interfaces provide the best user experience and performance for the exploration of 3D samples. We invited 12 skilled microscope operators to perform two different exploration tasks in 2D, 3D an

Negative / Null Result Report

Effect of remote surveillance system on management of diagnostic imaging significant actionable findings.

Jose A. Rivera, Carmen E. Gonzalez, Tonita Bates · 2024 · JCO Oncology Practice

327 Background: Delayed assessment of diagnostic imaging (DI) significant actionable findings (AFs) at an oncological center prompted the creation of a safety net system which used technological advancements to improve communication…

View details →DOI: 10.1200/op.2024.20.10_suppl.327
Negative / Null Result ReportOpen accessAgricultural and Biological Sciences

Optimizing fMRI Data Acquisition for Decoding Natural Speech with Limited Participants

Louis Jalouzot, Alexis Thual, Yair Lakretz et al. · 2025 · arXiv

We investigate optimal strategies for decoding perceived natural speech from fMRI data acquired from a limited number of participants. Leveraging Lebel et al. (2023)'s dataset of 8 participants, we first demonstrate the effectiveness of training deep neural networks to predict LLM-derived text representations from fMRI activity. Then, in this data regime, we observe that multi-subject training does not improve decoding accuracy compared to single-subject approach. Furthermore, training on similar or different stimuli across subjects has a negligible effect on decoding accuracy. Finally, we fin

Negative / Null Result ReportOpen accessComputer Science

Context-Aware Content Moderation for German Newspaper Comments

Felix Krejca, Tobias Kietreiber, Alexander Buchelt et al. · 2025 · arXiv

The increasing volume of online discussions requires advanced automatic content moderation to maintain responsible discourse. While hate speech detection on social media is well-studied, research on German-language newspaper forums remains limited. Existing studies often neglect platform-specific context, such as user history and article themes. This paper addresses this gap by developing and evaluating binary classification models for automatic content moderation in German newspaper forums, incorporating contextual information. Using LSTM, CNN, and ChatGPT-3.5 Turbo, and leveraging the One Mi

Negative / Null Result ReportOpen accessComputer Science

Fusion of Graph Neural Networks via Optimal Transport

Weronika Ormaniec, Michael Vollenweider, Elisa Hoskovec · 2025 · arXiv

In this paper, we explore the idea of combining GCNs into one model. To that end, we align the weights of different models layer-wise using optimal transport (OT). We present and evaluate three types of transportation costs and show that the studied fusion method consistently outperforms the performance of vanilla averaging. Finally, we present results suggesting that model fusion using OT is harder in the case of GCNs than MLPs and that incorporating the graph structure into the process does not improve the performance of the method.