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Browse the failure-mode index

21,770 real negative results, null findings, and replication failures. Search the index →

WASTE indexes published research — it does not host or republish full papers. Each entry is a metadata record compiled from open scholarly databases; the abstract is shown in full only where the paper is openly licensed, otherwise a short excerpt under fair use. Classifications are automated and approximate.

Replication Failure

Pyruvate and α-ketoglutarate precursor feeding combined with methyl jasmonate elicitation increases anthraquinone accumulation in hairy root cultures of Rubia tinctorum

Kalapuj Y, Perassolo M, Rodrïguez JM et al. · 2026 · Preprint

Abstract Anthraquinones (AQs) are specialized metabolites produced by Rubia tinctorum that have traditionally been used as dyes, but also have important biological activities. The present research studied the effects of the addition of…

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Negative / Null Result Report

Relationships between functional performance, body composition, and biochemical markers of stress, muscle damage, and inflammation in young men's team sport athletes. Implications for Game-Based Training

Widłak P, Malara M, Kuk A et al. · 2026 · Preprint

Abstract Movement quality and postural control are crucial for performance and injury prevention in team-sport athletes. Although FMS and YBT are commonly used, their ability to predict injury risk is limited when used alone. Therefore,…

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Negative / Null Result ReportOpen accessPhysics

From Light to Energy: Machine Learning Algorithms for Position and Energy Deposition Estimation in Scintillator-SiPM detectors

Yoav Simhon, Alex Segal, Ofer Amrani et al. · 2025 · arXiv

Scintillator-SiPM Particle Detectors (SSPDs) are compact, low-power devices with applications including particle physics, underground tomography, cosmic-ray studies, and space instrumentation. They are based on a prism-shaped scintillator with corner-mounted SiPMs. Previous work has demonstrated that analytic algorithms based on a physical model of light propagation can reconstruct particle impinging positions and tracks and estimate deposited energy and Linear Energy Transfer (LET) with moderate accuracy. In this study, we enhance this approach by applying machine learning (ML) methods, speci

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Negative / Null Result ReportOpen accessComputer Science

Evaluating Large Language Models for Time Series Anomaly Detection in Aerospace Software

Yang Liu, Yixing Luo, Xiaofeng Li et al. · 2026 · arXiv

Time series anomaly detection (TSAD) is essential for ensuring the safety and reliability of aerospace software systems. Although large language models (LLMs) provide a promising training-free alternative to unsupervised approaches, their effectiveness in aerospace settings remains under-examined because of complex telemetry, misaligned evaluation metrics, and the absence of domain knowledge. To address this gap, we introduce ATSADBench, the first benchmark for aerospace TSAD. ATSADBench comprises nine tasks that combine three pattern-wise anomaly types, univariate and multivariate signals, an

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Negative / Null Result ReportOpen accessComputer Science

Domain Decomposition Based High Performance Parallel Computing

Mandhapati P. Raju, Siddhartha Khaitan · 2009 · arXiv

The study deals with the parallelization of finite element based Navier-Stokes codes using domain decomposition and state-ofart sparse direct solvers. There has been significant improvement in the performance of sparse direct solvers. Parallel sparse direct solvers are not found to exhibit good scalability. Hence, the parallelization of sparse direct solvers is done using domain decomposition techniques. A highly efficient sparse direct solver PARDISO is used in this study. The scalability of both Newton and modified Newton algorithms are tested.

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Negative / Null Result ReportOpen accessPhysics

Adaptive elliptical aperture photometry: a software package for high-cadence ground-based photometry. I. Application to rapid oscillators observed from SAAO

Dominic M. Bowman, Daniel L. Holdsworth · 2019 · arXiv

Context. Modern space telescopes are currently providing high-precision light curves for a large fraction of the sky, such that many new variable stars are being discovered. However, some stars have periodic variability with periods of order minutes and require high-cadence photometry to probe the physical mechanisms responsible. A cadence of less than a minute is often required to remove Nyquist ambiguities and confirm rapid variability which forces observers to obtain high-cadence ground-based photometry. Aims. We aim to provide a modern software package to reduce ground-based photometric ti

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Negative / Null Result ReportOpen accessEconomics, Econometrics and Finance

Sanctions and Imports of Essential Goods: A Closer Look at the Equipo Anova (2021) Results

Francisco Rodríguez · 2022 · arXiv

We revisit the results of a recent paper by Equipo Anova, who claim to find evidence of an improvement in Venezuelan imports of food and medicines associated with the adoption of U.S. financial sanctions towards Venezuela in 2017. We show that their results are consequence of data coding errors and questionable methodological choices, including the use an unreasonable functional form that implies a counterfactual of negative imports in the absence of sanctions, the omission of data accounting for four-fifths of the country's food imports at the time of sanctions and incorrect application of re

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Failed Experiment ReportOpen accessComputer Science

Fragments in Gaussian Wave-Packet Dynamics with and without Correlations

P. Danielewicz, D. Kiderlen · 1997 · arXiv

Generalization of Gaussian trial wave functions in quantum molecular dynamics models is introduced, which allows for long-range correlations characteristic for composite nuclear fragments. We demonstrate a significant improvement in the description of light fragments with the correlations. Utilizing either type of Gaussian wave functions, with or without correlations, however, we find that we cannot describe fragment formation in a dynamic situation. Composite fragments are only produced in simulations if these fragments are present as clusters in the substructure of original nuclei. The diffi

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Replication FailureOpen accessComputer Science

Spin Transfer Torque Driven Coupled Oscillators for Self-Oscillating RF Mixers

Supriyo Maji · 2017 · arXiv

Spin transfer torque oscillators (STOs) based on magnetic tunnel junction (MTJ) devices are emerging as a possible replacement for complementary metal-oxide semiconductors for radio-frequency (RF) signal generation. Advantages include low power consumption, small device area, and large frequency tunability. But such a single device cannot achieve the necessary noise performance for RF applications. It has been reported lately that a network of globally coupled STOs achieves significant improvement in phase noise. The study here is to propose use of such coupled STOs as self-oscillating RF mixe

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Negative / Null Result ReportOpen accessPhysics

Large scale flows in the solar interior: Effect of asymmetry in peak profiles

Sarbani Basu, H. M. Antia · 1999 · arXiv

Ring diagram analysis can be used to study large scale velocity fields in the outer part of the solar convection zone. All previous works assume that the peak profiles in the solar oscillation power spectrum are symmetric. However, it has now been demonstrated that the peaks are not symmetric. In this work we study how the explicit use of asymmetric peak profiles in ring-diagram analysis influences the estimated velocity fields. We find that the use of asymmetric profiles leads to significant improvement in the fits, but the estimated velocity fields are not substantially different from those

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Negative / Null Result ReportOpen accessPhysics

Transiting Exoplanet Monitoring Project (TEMP). VI. The Homogeneous Refinement of System Parameters for 39 Transiting Hot Jupiters with 127 New Light Curves

Xian-Yu Wang, Yong-Hao Wang, Songhu Wang et al. · 2021 · arXiv

We present 127 new transit light curves for 39 hot Jupiter systems, obtained over the span of five years by two ground-based telescopes. A homogeneous analysis of these newly collected light curves together with archived spectroscopic, photometric, and Doppler velocimetric data using EXOFASTv2 leads to a significant improvement in the physical and orbital parameters of each system. All of our stellar radii are constrained to accuracies of better than 3\%. The planetary radii for 37 of our 39 targets are determined to accuracies of better than $5\%$. Compared to our results, the literature ecce

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Negative / Null Result ReportOpen accessComputer Science

Hadronic Contribution to (g-2)_{mu}

Andreas Hocker · 2001 · arXiv

The recent precise measurement of the muon magnetic anomaly (g-2)_{mu} at BNL opens a window into possible new physics, provided the contribution from hadronic vacuum polarization is well understood. This talk summarizes the development in the evaluation of the leading order hadronic contributions. Significant improvement has been achieved in a series of analyses which is presented historically in three steps: (1), use of tau spectral functions in addition to e+e- cross sections, (2), extended use of perturbative QCD and (3), application of QCD sum rule techniques. The uncertainties, in partic

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Negative / Null Result ReportOpen accessComputer Science

Good Data, Large Data, or No Data? Comparing Three Approaches in Developing Research Aspect Classifiers for Biomedical Papers

Shreya Chandrasekhar, Chieh-Yang Huang, Ting-Hao 'Kenneth' Huang · 2023 · arXiv

The rapid growth of scientific publications, particularly during the COVID-19 pandemic, emphasizes the need for tools to help researchers efficiently comprehend the latest advancements. One essential part of understanding scientific literature is research aspect classification, which categorizes sentences in abstracts to Background, Purpose, Method, and Finding. In this study, we investigate the impact of different datasets on model performance for the crowd-annotated CODA-19 research aspect classification task. Specifically, we explore the potential benefits of using the large, automatically

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Negative / Null Result ReportOpen accessComputer Science

Data filtering methods for training language models

Egor Shevchenko, Elena Bruches · 2026 · arXiv

Data quality is a critical factor in the effectiveness of machine learning models. Label errors, present even in widely used benchmarks, introduce noise into training data and reduce model generalization. In this work, we conduct a comparative analysis of two automatic label error detection methods - Confident Learning and Dataset Cartography - on three Russian text classification corpora of varying size, number of classes, and domain: ru_emotion_e-culture (49,123 examples, emotion classification), RuCoLA (8,524 examples, linguistic acceptability), and TERRa (2,337 examples, textual entailment

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Negative / Null Result ReportOpen accessPhysics

Cation mono- and co-doped anatase TiO$_2$ nanotubes: An {\em ab initio} investigation of electronic and optical properties

Mohamed M. Fadlallah, Ulrich Eckern · 2017 · arXiv

The structural, electronic, and optical properties of metal (Si, Ge, Sn, and Pb) mono- and co-doped anatase TiO$_{2}$ nanotubes are investigated, in order to elucidate their potential for photocatalytic applications. It is found that Si doped TiO$_{2}$ nanotubes are more stable than those doped with Ge, Sn, or Pb. All dopants lower the band gap, except the (Ge, Sn) co-doped structure, the decrease depending on the concentration and the type of dopant. Correspondingly, a redshift in the optical properties for all kinds of dopings is obtained. Even though a Pb mono- and co-doped TiO$_{2}$ nanotu

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Negative / Null Result ReportOpen accessPhysics

Astrophysical Prior Information and Gravitational-wave Parameter Estimation

Chris Pankow, Laura Sampson, Leah Perri et al. · 2016 · arXiv

The detection of electromagnetic counterparts to gravitational waves has great promise for the investigation of many scientific questions. It has long been hoped that in addition to providing extra, non-gravitational information about the sources of these signals, the detection of an electromagnetic signal in conjunction with a gravitational wave could aid in the analysis of the gravitational signal itself. That is, knowledge of the sky location, inclination, and redshift of a binary could break degeneracies between these extrinsic, coordinate-dependent parameters and the physical parameters,

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Negative / Null Result ReportOpen accessPhysics

Data-driven kinetic energy density fitting for orbital-free DFT: linear vs Gaussian process regression

Sergei Manzhos, Pavlo Golub · 2020 · arXiv

We study the dependence of kinetic energy densities (KED) on density-dependent variables that have been suggested in previous works on kinetic energy functionals (KEF) for orbital-free DFT (OF-DFT). We focus on the role of data distribution and on data and regressor selection. We compare unweighted and weighted linear and Gaussian process regressions of KED for light metals and a semiconductor. We find that good quality linear regression resulting in good energy-volume dependence is possible over density-dependent variables suggested in previous literature. This is achieved with weighted fitti

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Negative / Null Result ReportOpen accessComputer Science

Corrective In-Context Learning: Evaluating Self-Correction in Large Language Models

Mario Sanz-Guerrero, Katharina von der Wense · 2025 · arXiv

In-context learning (ICL) has transformed the use of large language models (LLMs) for NLP tasks, enabling few-shot learning by conditioning on labeled examples without finetuning. Despite its effectiveness, ICL is prone to errors, especially for challenging examples. With the goal of improving the performance of ICL, we propose corrective in-context learning (CICL), an approach that incorporates a model's incorrect predictions alongside ground truth corrections into the prompt, aiming to enhance classification accuracy through self-correction. However, contrary to our hypothesis, extensive exp

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Negative / Null Result ReportOpen accessComputer Science

Topic Level Disambiguation for Weak Queries

Hui Zhang, Kiduk Yang, Elin Jacob · 2015 · arXiv

Despite limited success, information retrieval (IR) systems today are not intelligent or reliable. IR systems return poor search results when users formulate their information needs into incomplete or ambiguous queries (i.e., weak queries). Therefore, one of the main challenges in modern IR research is to provide consistent results across all queries by improving the performance on weak queries. However, existing IR approaches such as query expansion are not overly effective because they make little effort to analyze and exploit the meanings of the queries. Furthermore, word sense disambiguati

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Negative / Null Result ReportOpen accessComputer Science

LLMs Corrupt Your Documents When You Delegate

Philippe Laban, Tobias Schnabel, Jennifer Neville · 2026 · arXiv

Large Language Models (LLMs) are poised to disrupt knowledge work, with the emergence of delegated work as a new interaction paradigm (e.g., vibe coding). Delegation requires trust - the expectation that the LLM will faithfully execute the task without introducing errors into documents. We introduce DELEGATE-52 to study the readiness of AI systems in delegated workflows. DELEGATE-52 simulates long delegated workflows that require in-depth document editing across 52 professional domains, such as coding, crystallography, and music notation. Our large-scale experiment with 19 LLMs reveals that cu

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