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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.

1761 results in Negative / Null Result Report for "Mpro" · page 43 of 59

Negative / Null Result ReportOpen access

Treatment outcomes of different prognostic groups of patients on cancer and leukemia group B trial 39801: induction chemotherapy followed by chemoradiotherapy compared with chemoradiotherapy alone for unresectable stage III non-small cell lung cancer

Akerley, Wallace, Herndon, James E. 2nd, Vokes, Everett E. et al. · 2017

BACKGROUND: In Cancer and Leukemia Group B 39801, we evaluated whether induction chemotherapy before concurrent chemoradiotherapy would result in improved survival and demonstrated no significant benefit from the addition of induction…

View details →DOI: 10.1097/jto.0b013e3181b27b33.
Negative / Null Result ReportOpen access

Treatment Outcomes of Different Prognostic Groups of Patients on Cancer and Leukemia Group B Trial 39801: Induction Chemotherapy Followed by Chemoradiotherapy Compared with Chemoradiotherapy Alone for Unresectable Stage III Non-small Cell Lung Cancer

Akerley, Wallace, Vokes, Everett E., Cicchetti, M Giulia et al. · 2009

BackgroundIn Cancer and Leukemia Group B 39801, we evaluated whether induction chemotherapy before concurrent chemoradiotherapy would result in improved survival and demonstrated no significant benefit from the addition of induction…

View details →DOI: 10.1097/jto.0b013e3181b27b33
Negative / Null Result ReportOpen access

Good laboratory practice: preventing introduction of bias at the bench

Macleod, Malcolm R.; id_orcid, Donnan, Geoffrey A., Traystman, RJ et al. · 2009

Background and Purpose—As a research community, we have failed to demonstrate that drugs which show substantial efficacy in animal models of cerebral ischemia can also improve outcome in human stroke. Summary of Review—Accumulating…

View details →DOI: 10.1038/jcbfm.2008.101
Negative / Null Result ReportOpen access

Subscriptions: Information about subscribing to Stroke is online at at UNIV OF EDINBURGH on Comments, Opinions, and Reviews Good Laboratory Practice Preventing Introduction of Bias at the Bench

Marc Fisher, Ulrich Dirnagl, Geoffrey A Donnan et al. · 2020

Background and Purpose-As a research community, we have failed to demonstrate that drugs which show substantial efficacy in animal models of cerebral ischemia can also improve outcome in human stroke. Summary of Review-Accumulating…

Negative / Null Result ReportOpen access

Feasibility of progesterone treatment for ischaemic stroke

Claire L. Gibson (6162488), Philip M. Bath (3111867) · 2015

Two multi-centre phase III clinical trials examining the protective potential of progesterone following traumatic brain injury have recently failed to demonstrate any improvement in outcome. Thus, it is timely to consider how this impacts…

Negative / Null Result ReportOpen access

Feasibility of progesterone treatment for ischaemic stroke

Claire L. Gibson (6162488), Philip M. Bath (3111867) · 2015

Two multi-centre phase III clinical trials examining the protective potential of progesterone following traumatic brain injury have recently failed to demonstrate any improvement in outcome. Thus, it is timely to consider how this impacts…

Negative / Null Result ReportOpen accessEngineering

Improving Power Flow Robustness via Circuit Simulation Methods

Amritanshu Pandey, Marko Jereminov, Gabriela Hug et al. · 2017 · arXiv

Recent advances in power system simulation have included the use of complex rectangular current and voltage (I-V) variables for solving the power flow and three-phase power flow problems. This formulation has demonstrated superior convergence properties over conventional polar coordinate based formulations for three-phase power flow, but has failed to replicate the same advantages for power flow in general due to convergence issues with systems containing PV buses. In this paper, we demonstrate how circuit simulation techniques can provide robust convergence for any complex I-V formulation tha

Negative / Null Result ReportOpen accessComputer Science

Perceptual compensation for tonal context in self-supervised speech models

James Kirby, Ioana Krehan, Michele Gubian · 2026 · arXiv

This study examines the extent to which the wav2vec2.0 architecture exhibits evidence of compensation for phonological context. We conducted a pseudo-replication of a perceptional compensation experiment on Mandarin Chinese tones, and compared the embedding similarities and probing classifier outputs between a purely self-supervised pre-trained model and a model fine-tuned for Mandarin ASR. No evidence of compensation was found in the embedding similarities of the purely pre-trained model. Probing classifiers showed some evidence of compensation in addition to the expected layer-wise improveme

Negative / Null Result ReportOpen accessComputer Science

An Empirical Examination of the Evaluative AI Framework

Jaroslaw Kornowicz · 2024 · arXiv

This study empirically examines the "Evaluative AI" framework, which aims to enhance the decision-making process for AI users by transitioning from a recommendation-based approach to a hypothesis-driven one. Rather than offering direct recommendations, this framework presents users pro and con evidence for hypotheses to support more informed decisions. However, findings from the current behavioral experiment reveal no significant improvement in decision-making performance and limited user engagement with the evidence provided, resulting in cognitive processes similar to those observed in tradi

Negative / Null Result ReportOpen accessPhysics

Results and forecasts on cosmic inflation from weak lensing

Agnès Ferté, Kevin Hong · 2023 · arXiv

We highlight the role of weak lensing measurements from current and upcoming stage-IV imaging surveys in the search for cosmic inflation, specifically in measuring the scalar spectral index $n_s$. To do so, we combine the Dark Energy Survey 3 years of observation weak lensing and clustering data with BICEP/Keck, Planck and Sloan Digital Sky Survey data in $rΛ$CDM where $r$ is the tensor-to-scalar ratio. While there is no significant improvement in constraining power, we obtain a 1$σ$ shift on $n_s$. Additionally, we forecast a weak lensing and clustering data vector from the 10-year Legacy Sur

Negative / Null Result ReportOpen accessComputer Science

Low Complexity V-BLAST MIMO-OFDM Detector by Successive Iterations Reduction

Karam Ahmed, Sherif Abuelenin, Heba Soliman et al. · 2015 · arXiv

V-BLAST detection method suffers large computational complexity due to its successive detection of symbols. In this paper, we propose a modified V-BLAST algorithm to decrease the computational complexity by reducing the number of detection iterations required in MIMO communication systems. We begin by showing the existence of a maximum number of iterations, beyond which, no significant improvement is obtained. We establish a criterion for the number of maximum effective iterations. We propose a modified algorithm that uses the measured SNR to dynamically set the number of iterations to achieve

Negative / Null Result ReportOpen accessComputer Science

Comparative Computational Strength of Quantum Oracles

Alp Atici · 2003 · arXiv

It is an established fact that for many of the interesting problems quantum algorithms based on queries of the standard oracle bring no significant improvement in comparison to known classical algorithms. It is conceivable that there are other oracles of algorithmic importance acting in a less intuitive fashion to which such limitations do not apply. Thus motivated this article suggests a broader understanding towards what a general quantum oracle is. We propose a general definition of a quantum oracle and give a classification of quantum oracles based on the behavior of the eigenvalues and ei

Negative / Null Result ReportOpen accessComputer Science

Can automated smoothing significantly improve benchmark time series classification algorithms?

James Large, Paul Southam, Anthony Bagnall · 2018 · arXiv

tl;dr: no, it cannot, at least not on average on the standard archive problems. We assess whether using six smoothing algorithms (moving average, exponential smoothing, Gaussian filter, Savitzky-Golay filter, Fourier approximation and a recursive median sieve) could be automatically applied to time series classification problems as a preprocessing step to improve the performance of three benchmark classifiers (1-Nearest Neighbour with Euclidean and Dynamic Time Warping distances, and Rotation Forest). We found no significant improvement over unsmoothed data even when we set the smoothing param

Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance

Talents from Abroad. Foreign Managers and Productivity in the United Kingdom

Dimitrios Exadaktylos, Massimo Riccaboni, Armando Rungi · 2020 · arXiv

In this paper, we test the contribution of foreign management on firms' competitiveness. We use a novel dataset on the careers of 165,084 managers employed by 13,106 companies in the United Kingdom in the period 2009-2017. We find that domestic manufacturing firms become, on average, between 7% and 12% more productive after hiring the first foreign managers, whereas foreign-owned firms register no significant improvement. In particular, we test that previous industry-specific experience is the primary driver of productivity gains in domestic firms (15.6%), in a way that allows the latter to ca

Negative / Null Result ReportOpen accessPhysics

Spatial resolution improvement of PICOSEC Micromegas precise timing detectors

F. M. Brunbauer, R. Aleksan, Y. Angelis et al. · 2026 · arXiv

The combination of a Cherenkov radiator with a semi-transparent photocathode and a Micromegas based amplification stage allows PICOSEC Micromegas detectors to achieve a time resolution of better than 15ps. While tileable prototypes with 10x10 channels feature 1x1 cm^2 readout pads, finer readout granularity can be used to improve the spatial resolution. We report on the study of high readout granularity PICOSEC Micromegas prototypes which achieve around 0.5mm spatial resolution with 3.5mm large pads. No significant improvement was found when readout pad size was further reduced to 2.2mm. The t

Negative / Null Result ReportOpen accessComputer Science

RegionGCN: Spatial-Heterogeneity-Aware Graph Convolutional Networks

Hao Guo, Han Wang, Di Zhu et al. · 2025 · arXiv

Modeling spatial heterogeneity in the data generation process is essential for understanding and predicting geographical phenomena. Despite their prevalence in geospatial tasks, neural network models usually assume spatial stationarity, which could limit their performance in the presence of spatial process heterogeneity. By allowing model parameters to vary over space, several approaches have been proposed to incorporate spatial heterogeneity into neural networks. However, current geographically weighting approaches are ineffective on graph neural networks, yielding no significant improvement

Negative / Null Result ReportOpen accessPhysics

Symmetric Operation of the Resonant Exchange Qubit

Filip K. Malinowski, Frederico Martins, Peter D. Nissen et al. · 2017 · arXiv

We operate a resonant exchange qubit in a highly symmetric triple-dot configuration using IQ-modulated RF pulses. At the resulting three-dimensional sweet spot the qubit splitting is an order of magnitude less sensitive to all relevant control voltages, compared to the conventional operating point, but we observe no significant improvement in the quality of Rabi oscillations. For weak driving this is consistent with Overhauser field fluctuations modulating the qubit splitting. For strong driving we infer that effective voltage noise modulates the coupling strength between RF drive and the qubi

Negative / Null Result ReportOpen accessPhysics

Photonic glass for high contrast structural color

Guoliang Shang, Lukas Maiwald, Hagen Renner et al. · 2018 · arXiv

Non-iridescent structural colors based on disordered arrangement of monodisperse spherical particles, also called photonic glass, show low color saturation due to gradual transition in reflectivity. No significant improvement is usually expected from particles optimization, as the Mie resonances are broad for small dielectric particles with moderate refractive index. Moreover, the short range order of a photonic glass alone is also insufficient to cause sharp spectral features. We show here, that the combination of a well-chosen particle geometry with the short range order of a photonic glass

Negative / Null Result ReportOpen accessComputer Science

How Do Large Language Models Acquire Factual Knowledge During Pretraining?

Hoyeon Chang, Jinho Park, Seonghyeon Ye et al. · 2024 · arXiv

Despite the recent observation that large language models (LLMs) can store substantial factual knowledge, there is a limited understanding of the mechanisms of how they acquire factual knowledge through pretraining. This work addresses this gap by studying how LLMs acquire factual knowledge during pretraining. The findings reveal several important insights into the dynamics of factual knowledge acquisition during pretraining. First, counterintuitively, we observe that pretraining on more data shows no significant improvement in the model's capability to acquire and maintain factual knowledge.

Negative / Null Result ReportOpen accessEngineering

Fast T2w/FLAIR MRI Acquisition by Optimal Sampling of Information Complementary to Pre-acquired T1w MRI

Junwei Yang, Xiao-Xin Li, Feihong Liu et al. · 2021 · arXiv

Recent studies on T1-assisted MRI reconstruction for under-sampled images of other modalities have demonstrated the potential of further accelerating MRI acquisition of other modalities. Most of the state-of-the-art approaches have achieved improvement through the development of network architectures for fixed under-sampling patterns, without fully exploiting the complementary information between modalities. Although existing under-sampling pattern learning algorithms can be simply modified to allow the fully-sampled T1-weighted MR image to assist the pattern learning, no significant improveme

Negative / Null Result Report

Ketamine shows no significant effect on PTSD symptoms in military

· 2022 · The Brown University Psychopharmacology Update

Eight infusions of ketamine administered over 4 weeks did not significantly improve symptoms of post‐traumatic stress disorder (PTSD) in a group of veterans and active‐duty military who had failed on prior antidepressant treatment, a…

View details →DOI: 10.1002/pu.30864
Negative / Null Result ReportOpen accessComputer Science

Semantic Table Detection with LayoutLMv3

Ivan Silajev, Niels Victor, Phillip Mortimer · 2022 · arXiv

This paper presents an application of the LayoutLMv3 model for semantic table detection on financial documents from the IIIT-AR-13K dataset. The motivation behind this paper's experiment was that LayoutLMv3's official paper had no results for table detection using semantic information. We concluded that our approach did not improve the model's table detection capabilities, for which we can give several possible reasons. Either the model's weights were unsuitable for our purpose, or we needed to invest more time in optimising the model's hyperparameters. It is also possible that semantic inform

Negative / Null Result ReportOpen accessComputer Science

Post-processing Multi-Model Medium-Term Precipitation Forecasts Using Convolutional Neural Networks

Bob de Ruiter · 2021 · arXiv

The goal of this study was to improve the post-processing of precipitation forecasts using convolutional neural networks (CNNs). Instead of post-processing forecasts on a per-pixel basis, as is usually done when employing machine learning in meteorological post-processing, input forecast images were combined and transformed into probabilistic output forecast images using fully convolutional neural networks. CNNs did not outperform regularized logistic regression. Additionally, an ablation analysis was performed. Combining input forecasts from a global low-resolution weather model and a regiona

Negative / Null Result ReportOpen accessComputer Science

Self-Supervised Learning for Knee Osteoarthritis: Diagnostic Limitations and Prognostic Value of Hospital Data

Haresh Rengaraj Rajamohan, Yuxuan Chen, Kyunghyun Cho et al. · 2026 · arXiv

This study assesses whether self-supervised learning (SSL) improves knee osteoarthritis (OA) modeling for diagnosis and prognosis relative to ImageNet-pretrained initialization. We compared (i) image-only SSL pretrained on knee radiographs from the OAI, MOST, and NYU cohorts, and (ii) multimodal image-text SSL pretrained on hospital knee radiographs paired with radiologist impressions. For diagnostic Kellgren-Lawrence (KL) grade prediction, SSL yielded mixed results. While image-only SSL improved accuracy during linear probing (frozen encoder), it did not outperform ImageNet pretraining during

Negative / Null Result ReportOpen accessComputer Science

Hunting for Axionlike Dark Matter by Searching for an Oscillating Neutron Electric Dipole Moment

N. J. Ayres · 2018 · arXiv

We report on a search for ultra-low-mass axion-like dark matter by analysing the ratio of the spin-precession frequencies of stored ultracold neutrons and $^{199}$Hg atoms for an axion-induced oscillating electric dipole moment of the neutron and an axion-wind spin-precession effect. No signal consistent with dark matter is observed for the axion mass range $10^{-24}~\textrm{eV} \le m_a \le 10^{-17}~\textrm{eV}$. Our null result sets the first laboratory constraints on the coupling of axion dark matter to gluons, which improve on astrophysical limits by up to 3 orders of magnitude, and also im

Negative / Null Result ReportOpen accessPhysics

Probing Dark Energy Inhomogeneities with Supernovae

Michael Blomqvist, Edvard Mortsell, Serena Nobili · 2008 · arXiv

We discuss the possibility to identify anisotropic and/or inhomogeneous cosmological models using type Ia supernova data. A search for correlations in current type Ia peak magnitudes over a large range of angular scales yields a null result. However, the same analysis limited to supernovae at low redshift, shows a feeble anticorrelation at the two sigma level at angular scales of about 40 degrees. Upcoming data from, e.g., the SNLS (Supernova Legacy Survey) and the SDSS-II (SDSS: Sloan Digital Sky Survey) supernova searches will improve our limits on the size of - or possibly detect - possible