SolvedByAI

Queue

628 cases were harvested and are backed by a real paper, but they fail the test the index publishes on. Each one is listed here with the reason, so the exclusion can be checked rather than trusted.

All 628 assisted 358 not a result 183 unsupported 87
Paper Year Cited Why it is held
Topology-Preserving Deep Image Segmentation arXiv (Cornell University) 2019 114 unsupported no abstract available for this DOI
Optimization of Silicone 3D Printing with Hierarchical Machine Learning 3D Printing and Additive Manufacturing 2019 111 assisted The HML model recommended optimal formulations and processing parameters within a human-run experimental pipeline (38 physical trial runs plus human printing and fidelity validation), so the AI informed an optimization workflow rather than performing the printing task itself. “the FRE method for 3D printing silicone parts was optimized based on a training set with 38 trial runs”
Innovations in Camera Trapping Technology and Approaches: The Integration of... Animals 2020 110 not a result This is a review/commentary proposing future integration of citizen science and AI for camera trap classification, with no primary result produced by an AI system. “We propose, as a solution, more efforts to combine citizen science with AI to improve classification accuracy and efficiency while maintaining public...”
Maize yield forecasting by linear regression and artificial neural networks... The Journal of Agricultural Science 2014 100 assisted The ANN is one of several statistical tools (alongside MLR and persistence) inside a human-designed forecasting study whose contribution is a comparative skill evaluation and methodological findings, not an AI-produced result that itself constitutes the paper's achievement. “Forecasting the maize yield of China's Jilin province from 1962 to 2004... was investigated using multiple linear regression (MLR) and non-linear arti...”
Deep-learning based denoising and reconstruction of super-resolution structu... Photonics Research 2021 96 unsupported no abstract available for this DOI
RPITER: A Hierarchical Deep Learning Framework for ncRNA–Protein Interaction... International Journal of Molecular Sciences 2019 96 assisted The paper reports a prediction model's benchmark accuracy (AUC on five existing RPI datasets) as a computational aid for biological research, explicitly framing itself as a complementary tool rather than an agent that solved the biological problem of identifying ncRNA, protein interactions. “The proposed RPITER could be a complementary method for predicting RPI and constructing RPI network, which would help push forward the related biologi...”
Quantum machine learning for particle physics using a variational quantum cl... Journal of High Energy Physics 2021 87 assisted The paper's contribution is a human-designed hybrid variational quantum classifier benchmarked on a particle-physics classification task, where the classifier is one component inside a human-run resonance-search analysis rather than an AI that itself solved the physics problem. “By applying this algorithm to a resonance search in di-top final states, we find that this method has a better learning outcome than a classical neura...”
Imaging in focus: An introduction to denoising bioimages in the era of deep... The International Journal of Biochemistry & Cell Biology 2021 82 not a result This is a review/survey introducing deep-learning denoising methods for microscopy, with no primary result produced by an AI system. “In this review, we first describe the different types of noise that typically corrupt fluorescence microscopy images and introduce the denoising task.”
The Effects of Explanations in Automated Essay Scoring Systems on Student Tr... Journal of Learning Analytics 2023 76 assisted The paper's primary result is a human-factors finding about student trust and motivation, produced by a human-designed user study in which the automated essay scoring system was merely the stimulus/object under investigation rather than the agent producing the result. “The current study aimed to identify the effect of explanations of an automated essay scoring system on students' trust and motivation.”
Explaining deep neural networks for knowledge discovery in electrocardiogram... Scientific Reports 2021 75 assisted The paper presents an explainability method (ECGradCAM) whose attention maps are explicitly framed as aids for human clinicians and researchers who remain responsible for decisions and knowledge discovery, with the AI output informing humans rather than solving a task end-to-end. “Attention maps may be used in the clinic to aid diagnosis, discover new medical knowledge, and identify novel features and characteristics of medical...”
Advancing Enzyme’s Stability and Catalytic Efficiency through Synergy of For... ACS Catalysis 2023 75 assisted The computational tools (FireProt, PROSS, machine learning) served as design-prediction components within a human-run protein engineering workflow that included manual curation, wet-lab construction, and crystallographic validation, rather than an AI itself producing the stabilized enzymes. “their prediction accuracy can be improved by applying manual curation or machine learning for the removal of potentially destabilizing mutations, yiel...”
Laser-Induced Breakdown Spectroscopy Assisted by Machine Learning for Plasti... Atoms 2019 72 assisted The ML algorithms (PCA/LDA) function as data-analysis components inside a human-designed and human-run LIBS experimental workflow, reporting classification accuracies on curated lab samples as a technique demonstration, with the actual sorting/recycling application left prospective. “The combination of LIBS technique with these machine learning algorithmic approaches, in particular the latter, provided excellent classification resu...”
Clustering-Based Selection for the Exploration of Compiler Optimization Sequ... ACM Transactions on Architecture and Code Optimization 2016 70 unsupported no abstract available for this DOI
Machine-Learning-Guided Library Design Cycle for Directed Evolution of Enzym... ACS Catalysis 2021 70 assisted The ML only predicted variant libraries within a human-run directed evolution pipeline where humans performed the mutagenesis, experimental activity assays, and iterative wet-lab evaluation, so the improved enzymes were produced by the human workflow rather than by the AI end to end. “variants predicted by the first round were experimentally evaluated, and used as additional training data for the second-round prediction”
A Hybrid Flux Balance Analysis and Machine Learning Pipeline Elucidates Meta... iScience 2020 68 assisted The ML pipeline (FBA, PCA, k-means, LASSO) is one component in a human-run analysis workflow whose biological conclusions about cyanobacterial adaptation are drawn by the authors, not autonomously produced as the paper's primary result. “We then incorporate principal-component analysis, k-means clustering, and LASSO regularization to reduce dimensionality and extract key cross-omic fea...”
neu Print: Analysis Tools for EM Connectomics bioRxiv (Cold Spring Harbor Laboratory) 2020 66 not a result The paper introduces a database and analysis toolkit for connectome data rather than reporting a primary scientific result produced by an AI system; its contribution is enabling infrastructure demonstrated only via example queries. “We introduce neuPrint to address these data analysis challenges. neuPrint is a database and analysis ecosystem that organizes connectome data in a man...”
Deep Learning-Based Weed Detection Using UAV Images: A Comparative Study Drones 2023 65 not a result The paper's contribution is a comparative benchmark re-running established segmentation models (SegNet, UNet, DeepLabV3+ with standard backbones) on a dataset to recommend a model, not a new AI-produced result or capability. “we perform a comparative study of cutting-edge AI deep learning-based segmentation models for weed detection using an RGB image dataset acquired with...”
AptaNet as a deep learning approach for aptamer–protein interaction predicti... Scientific Reports 2021 65 assisted AptaNet is a predictive model evaluated only on a constructed benchmark (reporting accuracy metrics), with the abstract explicitly framing it as a tool that 'can help identify' novel pairs rather than an agent that discovered or validated any aptamer, protein interactions itself. “The results indicate that AptaNet can help identify novel aptamer–protein interacting pairs”
The major effects of health-related quality of life on 5-year survival predi... Scientific Reports 2020 63 assisted The ML models are a methodological component in a human-designed prognostic modeling study whose actual contribution is the analytical finding that adding HRQOL variables improves survival prediction accuracy, not an AI-produced result standing on its own. “The primary goal of this study was to evaluate the major roles of health-related quality of life (HRQOL) in a 5-year lung cancer survival prediction m...”
The Framing of machine learning risk prediction models illustrated by evalua... npj Digital Medicine 2021 61 not a result The paper's contribution is methodological guidance on problem framing concepts, using a sepsis model only as an illustrative example to show framing effects on evaluation, not as a system that solved a clinical prediction task. “it is important to assess the results of objective evaluations within the context of more subjective evaluations of how a model is framed”
Sweet corn yield prediction using machine learning models and field-level da... Precision Agriculture 2023 60 assisted The ML models are tools inside a human-run analysis whose stated goals are to benchmark model performance and extract variable-importance insights from historical data, not to deliver an end-to-end solved prediction capability. “This study utilizes a historic US sweet corn dataset to: (a) evaluate machine learning model performances on sweet corn yield prediction and (b) ident...”
Macrocyclization of linear molecules by deep learning to facilitate macrocyc... Nature Communications 2023 56 assisted Macformer is a generative component whose outputs were then filtered by human-run docking and wet-lab validation to design JAK2 inhibitors, making the AI one step in a human-driven pipeline rather than the end-to-end solver. “We showcase the utility of Macformer when combined with molecular docking simulations and wet lab based experimental validation, by applying it to the...”
Automated detection of European wild mammal species in camera trap images wi... European Journal of Wildlife Research 2020 55 assisted The paper is a human-run usability test of an existing, pre-trained TensorFlow Hub model, reporting its accuracy figures and framing the outcome as 'potential' for speeding up human camera-trap analysis (with further training needed), rather than the AI itself delivering a solved capability. “we have shown the potential of an existing and pre-trained image classification model for wildlife animal detection, classification, and analysis”
Simulated Design–Build–Test–Learn Cycles for Consistent Comparison of Machin... ACS Synthetic Biology 2023 54 not a result The paper's contribution is a simulation/benchmarking framework for comparing ML methods in DBTL cycles, not an AI-produced solution to an actual metabolic engineering problem. “we propose a mechanistic kinetic model-based framework to test and optimize machine learning for iterative combinatorial pathway optimization”
Fabric Defect Detection in Real World Manufacturing Using Deep Learning Information 2024 53 assisted The paper's primary result is a performance comparison of off-the-shelf detection models (YOLOv8/v5, MobileNetV2-SSD) on a newly collected textile dataset, i.e., reported accuracy on an existing task where the model serves as a component to assist human quality inspection rather than the AI itself being the contribution that solved the manufacturing defect problem. “YOLOv8n achieved the highest performance, with a mAP of 84.8%, precision of 0.818, and recall of 0.839 across seven different defect classes.”
Automated generation of discharge summaries: leveraging large language model... Scientific Reports 2025 53 assisted The LLM only produced editable draft summaries for physicians to review and correct within a human-run workflow (data manually extracted from EHRs, outputs rated and finalized by humans), and the paper itself frames its contribution as descriptive insights to guide future work rather than a demonstrated solved capability, with frequent errors and omissions reported. “the goal is to assist physicians with editable draft summaries”
A novel deep learning model based on convolutional neural networks for emplo... Journal of Forecasting 2021 52 unsupported no abstract available for this DOI
Evaluation Framework of Large Language Models in Medical Documentation: Deve... Journal of Medical Internet Research 2024 52 not a result The paper's contribution is a human-developed evaluation framework for judging LLM-generated records, a methodological toolkit that enables future work, while the LLM serves only as the object being assessed (and found error-prone), not an agent that solved any problem. “This study aimed to develop and validate an evaluation framework for assessing the accuracy and clinical applicability of LLM-generated emergency depa...”
Machine learning for faster and smarter fluorescence lifetime imaging micros... Journal of Physics Photonics 2020 51 not a result The abstract explicitly describes a topical review summarizing ML methods for FLIM rather than presenting a primary result where an AI system solved a problem. “In this topical review, we first discuss the basics of FILM and ML.”
On Efficiency of Selected Machine Learning Algorithms for Intrusion Detectio... International Journal of Electronics and Telecommunications 2016 50 assisted The paper's contribution is a concept and evaluation environment in which humans test and compare ML algorithms' detection efficiency on generated SDN traffic, making the AI a component of a human-run benchmarking workflow rather than the agent that solved intrusion detection. “The article examines the efficiency of selected machine learning methods: Self Organizing Maps and Learning Vector Quantization and their enhanced ver...”
Pill Detection Model for Medicine Inspection Based on Deep Learning Chemosensors 2021 48 assisted The abstract reports a deep learning model's benchmark-style detection improvement over existing algorithms, with the AI explicitly framed as a component that will aid the human-run medicine inspection workflow rather than itself completing inspection end to end. “Our proposed method will help minimize problems, such as loss of productivity and human error, which occur while inspecting dispensed pills.”
Additive manufacturing: A machine learning model of process-structure-proper... Materials Science in Additive Manufacturing 2022 47 assisted The ML model is a predictive correlation component inside a human-driven experimental workflow (humans fabricated samples, characterized microstructure via SEM/EBSD/XRD, and ran Taguchi machining tests), and the reported result is the model's prediction accuracy on that human-collected data rather than the AI performing the task end to end. “It was found that the prediction accuracy of this new PSP linkage is extremely high (>99%, statistically significant at 95% confidence interval).”
Multi-Feature Classification of Multi-Sensor Satellite Imagery Based on Dual... Sensors 2018 46 assisted The random forest classifier is a standard off-the-shelf tool embedded in a human-designed feature-engineering and sensor-comparison workflow, and the paper's contribution is the comparative accuracy analysis of feature/sensor combinations rather than a new AI capability or an AI-produced result. “The classification was performed using a random forest (RF) method.”
Using machine learning to partition streaming programs ACM Transactions on Architecture and Code Optimization 2013 46 unsupported no abstract available for this DOI
Trends in forensic microbiology: From classical methods to deep learning Frontiers in Microbiology 2023 45 not a result The abstract explicitly identifies the paper as a review summarizing existing applications of forensic microbiology and ML/DL methods, with no primary result produced by an AI system. “This review summarizes the application and development of forensic microbiology, as well as the research progress of machine learning (ML) and deep le...”
Comparison of neural network and support vector machine methods for Kp forec... Journal of Geophysical Research Space Physics 2013 45 unsupported no abstract available for this DOI
Deep learning enables fast, gentle STED microscopy Communications Biology 2023 44 unsupported no abstract available for this DOI
A Machine Learning Classifier for Fast Radio Burst Detection at the VLBA Publications of the Astronomical Society of the Pacific 2016 44 assisted The classifier is a filtering component in a human-run candidate review pipeline, humans still review and decide on the most promising candidates, so the AI aids rather than completes the discovery workflow. “leaving only the 10%–20% most promising candidates to be reviewed by humans”
Automated visitor and wildlife monitoring with camera traps and machine lear... Remote Sensing in Ecology and Conservation 2023 42 assisted This is a validation study of an existing open-source model (MegaDetector) whose outputs are benchmarked against human manual classifications within a human-run camera-trap workflow, so the AI is an evaluated component of the pipeline rather than the agent that produced the paper's primary result. “The performance at detecting and counting humans, animals and vehicles is evaluated by comparing the detection results with manual classifications of...”
ARPEGE Cloud Cover Forecast Postprocessing with Convolutional Neural Network Weather and Forecasting 2020 40 unsupported no abstract available for this DOI