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Good Space a ranking of the record

TheGood surrounding AI

101 gains match this view. 94% rest on at least one peer-reviewed study, and 17% clear the high-evidence bar. The latest was filed Oct 16, 2026.

Every gain in this view, one square each, shaded by the strength of its evidence. High 17 Moderate 84 Emerging 0
101 results
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Sector: science

Matching records · page 3 of 4

61
Evidence-backed gainPeer-reviewedClimate

Ensemble ML with SHAP clustering achieved R2=0.913 on 2020-2023 regulatory data and identified ten recurrent environmental settings driving PM10, enabling interpretable analysis without chemical speciation.

Source article: Beyond concentration-based analysis: explainable AI identifies environmental settings influencing urban PM 10 variability

Science of The Total Environment
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62
Evidence-backed gainPeer-reviewedClimate

A probabilistic causal machine learning framework trained on long-term monitoring data from a full-scale wastewater plant can predict N2O hot moments and convert interpretable outputs into risk-decision rules for adaptive aeration and load regulation to reduce emissions.

Source article: Identifying causal pathways and risk-decision rules for nitrous oxide emission hot moments in wastewater treatment plants using probabilistic causal machine learning

Bioresource Technology
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63
Evidence-backed gainPeer-reviewedScience

A delta-ML graph neural network using GFN2-xTB geometries and DFT single-points as low-fidelity inputs predicted PBE0-D3BJ and PBE-D3BJ level properties of transition metal complexes with higher accuracy and better data efficiency than a conventional benchmark.

Source article: Δ -Machine Learning for the Prediction of Metal Complex Properties

Chemistry – A European Journal
Reader signal

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64
Evidence-backed gainPeer-reviewedScience

Researchers built a DPMD-based machine learning force field with active learning for FLiBeU fuel salt and used it to systematically compute microstructure, thermophysical and transport properties across 773-1173 K and 3-50 mol% UF4.

Source article: Machine learning force field development and basic physical property studies for molten salt reactor fuel salt LiF-BeF<sub>2</sub>-UF<sub>4</sub>

Physical Chemistry Chemical Physics
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65
Evidence-backed gainPeer-reviewedScience

Generative AI applied to supply chain and operations management can enhance decision-making and optimize processes across areas like demand forecasting and inventory management to improve efficiency, accuracy, and resilience.

Source article: Generative artificial intelligence in supply chain and operations management: a capability-based framework for analysis and implementation

International Journal of Production Research
Reader signal

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66
Evidence-backed gainPeer-reviewedScience

An ensemble combining Random Forest and Multi-Layer Perceptron improved genomic prediction of residual feed intake in 220 UK Holstein cows to R2=0.39 and RMSE=0.086, outperforming conventional gBLUP.

Source article: Integrating multi-layer perceptron and random forest in an ensemble framework for improved genomic prediction accuracy and SHAP-derived interpretability of residual feed intake in cattle

Journal of Animal Science and Biotechnology
Reader signal

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67
Evidence-backed gainPeer-reviewedScience

Generative AI tools, especially ChatGPT chatbots, were associated with enhanced institutional performance and work productivity across sectors including academia, research, technology, communications, agriculture, government, and business as of early 2024.

Source article: Enhancing Work Productivity through Generative Artificial Intelligence: A Comprehensive Literature Review

Sustainability
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68
Evidence-backed gainPeer-reviewedClimate

Machine learning models combined with fuzzy logic integration improved prediction of flood, avalanche, rockfall and landslide susceptibility in a mountainous region of northern Iran, with RF and AND operator achieving highest reliability for spatial planning.

Source article: Distinguishing compound and cumulative hazards using machine learning and fuzzy logic in multi-hazard susceptibility mapping

Scientific Reports
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69
Evidence-backed gainPeer-reviewedScience

Automated vision system SolenopsisDetector can localize fire ants and classify Solenopsis species from images, with whole-body detection reaching high mAP and thorax/abdomen crops improving classification accuracy.

Source article: SolenopsisDetector: development of an automatic detection system for fire ants using computer vision and deep learning

Journal of Economic Entomology
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70
Evidence-backed gainPeer-reviewedClimate

Hybrid STICS plus random forest integration improved accuracy and interpretability of apple fruit maturity date prediction to support harvest timing and climate adaptation across China's apple regions.

Source article: Coupling machine learning with a biophysical model for maturity date prediction of apple fruit across China's apple planting regions

Journal of the Science of Food and Agriculture
Reader signal

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71
Evidence-backed gainPeer-reviewedScience

LLM-driven adaptive level modification framework classified players by skill with 97.82% accuracy and generated modified levels that remained traversable at 74.1% full-level and 83.5% chunk-level rates.

Source article: Adaptive level modification via player skill classification and large language models

Scientific Reports
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72
Evidence-backed gainPeer-reviewedScience

Release of SynTabFall synthetic dataset with 745,380 samples allows training fall-risk prediction models without original patient data while achieving performance on par with models trained on real data.

Source article: Anonymized but Useful Synthetic Tabular Health Data for AI based Fall Risk Assessment

Scientific Data
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73
Evidence-backed gainPeer-reviewedScience

EMFF-2025 provides DFT-level accuracy for structure, mechanical properties, and decomposition across 20 C, H, N, O energetic materials while enabling faster iteration than first-principles methods.

Source article: EMFF-2025: a general neural network potential for energetic materials with C, H, N, and O elements

npj Computational Materials
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75
Evidence-backed gainPeer-reviewedScience

Integrating AI across 6G network layers enables optimized resource allocation and improved efficiency, with future networks providing AI as a service for immersive communication and industrial robots.

Source article: Overview of AI and communication for 6G network: fundamentals, challenges, and future research opportunities

Science China Information Sciences
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77
Evidence-backed gainPeer-reviewedScience

DynStabNet E(3)-equivariant graph neural network predicts dynamical stability of semiconductor crystal candidates without explicit phonon calculations at inference, achieving 97% accuracy and cutting per-structure evaluation from hours to ~1 ms to accelerate large-scale screening.

Source article: DynStabNet: A Deep Learning Framework for Fast Dynamical Stability Prediction of Crystal Structures

The Journal of Physical Chemistry Letters
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78
Evidence-backed gainPeer-reviewedClimate

IoT-enabled real-time data collection combined with machine learning analysis enables accurate predictions of water quality to support safeguarding decisions and preventive measures against contamination.

Source article: Advances in machine learning and IoT for water quality monitoring: A comprehensive review

Heliyon
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81
Evidence-backed gainPeer-reviewedScience

Machine learning accelerates solid-state electrolyte development by efficiently predicting ionic conductivity, elastic moduli, and thermodynamic stability to enable rapid next-generation design.

Source article: Applications and Advances of Machine Learning in the Development of Solid-State Electrolytes for Lithium-Ion Batteries

ACS Omega
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83
Evidence-backed gainPeer-reviewedScience

Self-optimizing attention-coupled neural network potential automates crystal structure prediction and iteratively refines itself, enabling exploration of nearly 10 million configurations with ab initio accuracy and substantial speedup over first-principles calculations.

Source article: Self-optimizing machine learning potential assisted automated workflow for highly efficient complex systems material design

npj Computational Materials
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84
Evidence-backed gainPeer-reviewedScience

Integration of AI with databases, theory and automation enables systematic predictive materials discovery by identifying complex structure-property relationships and closing the loop between prediction and validation.

Source article: Digital materials ecosystem: from databases to AI agents for autonomous discovery

Chemical Science
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85
Evidence-backed gainPeer-reviewedClimate

AI applications in urban planning and disaster management are being used to help city officials make informed decisions and optimize resource usage to improve quality of life for urban residents.

Source article: The smart future for sustainable development: Artificial intelligence solutions for sustainable urbanization

Sustainable Development
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86
Evidence-backed gainPeer-reviewedScience

LLM analysis of 355 articles to extract chemical relationships guided selection of building blocks and thiazole linkage to synthesize Thz-COF that produces high-concentration H2O2.

Source article: Synthesis of covalent organic frameworks for photocatalytic hydrogen peroxide production guided by large language models

Nature Communications
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87
Evidence-backed gainPeer-reviewedScience

GPT-3.5 and especially GPT-4 produced narratives that were more progressive on gender roles and sexuality than human crowdworker narratives when responding to identical prompts about creating and falling in love with an artificial human.

Source article: Experimental narratives: A comparison of human crowdsourced storytelling and AI storytelling

Humanities and Social Sciences Communications
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