explainable ai

Multimodal Satellite and Environmental Exposure Dataset for US County Life Expectancy (CONUS 2003–2019): Predictive Multiplicity in Environmental Health

Multimodal Satellite and Environmental Exposure Dataset for US County Life Expectancy (CONUS 2000–2023): Predictive Multiplicity in Environmental Health This repository provides the harmonized multimodal environmental dataset supporting the manuscript "Predictive Multiplicity in Environmental Health: Information Theory...

Introduction to Google Gemini

This chapter provides a comprehensive introduction to Google Gemini, describing it as a family of powerful, multimodal large language models (LLMs) capable of processing and reasoning across text, images, audio, video, and code. It highlights Gemini’s evolution from earlier models like Bard (built on LaMDA and PaLM) to...

Analytical Results Map: From AI Ethics Principles to Implementation Commons

This report maps the analytical results of From AI Ethics Principles to Implementation Commons, version 1.1. Prepared by the paper’s author, it identifies 69 linked results and intermediate conclusions organised into 12 analytical chains. The map covers the reconstruction of public interest, AI complementarity and smar...

Organisational culture and technology acceptance as catalysts for artificial intelligence adoption towards human resource management effectiveness in Thailand’s industrial hubs

Orientation: Artificial intelligence (AI) is becoming increasingly important in human resource management (HRM), particularly in Thailand’s Eastern Economic Corridor (EEC), a rapidly developing industrial and economic zone. Identifying the key factors that influence AI adoption can help organisations improve the effect...

Peer Review Report For: Towards Sustainable Vocational Education: An Explainable Green AI Ecosystem for Workforce Readiness [version 1; peer review: 2 approved with reservations]

Background Vocational education increasingly requires the integration of artificial intelligence-supported learning and sustainability competencies to prepare students for technology-intensive and environmentally responsible workplaces. However, limited empirical evidence exists on learning ecosystems that combine expl...

Exploring the moderating effects of flow experience in strengthening artificial intelligence-based customer interactions on social commerce

Purpose This study aims to investigate the effect of utilizing artificial intelligence (AI) in social commerce on increasing consumer engagement, specifically in terms of engagement and conversion rates. It also examines the role of flow experience in strengthening this relationship. Design/methodology/approach This st...

A Computational Workflow Integrating Explainable AI and Database Mining for the Prioritization of Antimicrobial Natural Products

The escalating threat of antimicrobial resistance demands the discovery of antibacterial agents with unprecedented chemical scaffolds. Natural products have historically been the most prolific source of antibiotics, yet the vast majority of catalogued natural products remain untested for antimicrobial activity. Here we...

A computationally-integrated simulation-focused problem-based learning framework for engineering dynamics: design, implementation, and mixed-methods evaluation in an OBE-aligned undergraduate course

Engineering dynamics courses demand simultaneous development of mathematical modelling, computational implementation, and communication competencies, yet conventional instruction rarely provides authentic contexts for their integration. The primary objective of this study was to design, implement, and empirically eva...

Beyond the Black Box: A Semantic Explainable AI Framework for Transparent and Trustworthy E-

Artificial intelligence has become an important part of modern e-commerce, supporting product recommendations, search ranking, customer-review analysis, and personalized shopping experiences. Despite these benefits, customers often receive recommendations without understanding the reasons behind them. This lack of tran...

Correction: Tumor-immune microenvironment and nutritional status biomarkers predict recurrence after total colectomy for locally advanced colon cancer: development and internal validation of a nomogram

Query no.Author's response as the author, to ensure you have permission to use the images in the article.Please check this link for information on author responsibilities and the publication images. �Please provide the names of the remaining authors in becht et al., 2012. Frontiers guidelines require to list at least 6...

Agentic Displacement in Second Language Writing: The Acquisitional Consequences of Delegating Writing to Autonomous AI Browsers

Autonomous AI browsers such as Perplexity Comet and Copilot Mode in Microsoft Edge can receive a writing assignment, draft a response, and submit it with little language produced by the learner. To explain what this means for second language (L2) writing, this conceptual paper introduces the term agentic displacement....

Interpretability Methods for Causal Predictions in Biomedical AI: A Systematic Review of Approaches and Evaluation Practices