{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_studyx","slug":"studyx","name":"StudyX","type":"product","url":"https://studyx.ai","page_url":"https://unfragile.ai/studyx","categories":["research-search"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_studyx__cap_0","uri":"capability://search.retrieval.semantic.paper.search.across.200m.academic.corpus","name":"semantic-paper-search-across-200m-academic-corpus","description":"Searches a 200M+ paper database using semantic similarity matching (likely embedding-based retrieval) rather than keyword indexing, enabling discovery of papers by research concept rather than exact title/author match. The system likely ingests paper metadata (abstracts, titles, authors) into a vector store and performs approximate nearest-neighbor search to surface relevant literature. Integration with citation graphs allows discovery of related work through co-citation patterns.","intents":["Find papers on a research topic when I don't know the exact terminology or key authors","Discover related work and citations for a literature review without manually following citation chains","Search across multiple academic domains (computer science, biology, physics, etc.) with a single query"],"best_for":["Undergraduate and graduate students conducting literature reviews","Researchers exploring adjacent domains without deep domain expertise","Non-academic professionals needing quick access to peer-reviewed research"],"limitations":["200M corpus may have incomplete coverage of recent papers (lag time between publication and indexing typically 3-6 months)","Semantic search quality depends on embedding model quality; may miss papers using non-standard terminology","No advanced filtering by publication date, journal impact factor, or citation count visible in product description","Cannot guarantee full-text access to papers; many results likely point to paywalled content requiring institutional access"],"requires":["Internet connection for real-time search","Account creation (freemium tier available)","No specific API key or authentication beyond platform login"],"input_types":["natural language query (e.g., 'transformer architectures for time series forecasting')","paper title or DOI for related work discovery"],"output_types":["ranked list of papers with metadata (title, authors, abstract, publication year)","direct links to paper PDFs or abstract pages","citation context snippets showing how papers reference each other"],"categories":["search-retrieval","academic-research"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_studyx__cap_1","uri":"capability://text.generation.language.ai.powered.research.synthesis.chatbot","name":"ai-powered-research-synthesis-chatbot","description":"Conversational AI interface that accepts research questions and synthesizes answers by querying the 200M paper database, extracting relevant findings, and generating natural language summaries with citations. The system likely uses a retrieval-augmented generation (RAG) pipeline: user query → semantic search across papers → LLM-based synthesis of results → citation attribution. Maintains conversation context across multiple turns to allow follow-up questions and clarification.","intents":["Ask a research question in natural language and get a synthesized answer with citations to supporting papers","Explore a topic iteratively through follow-up questions without re-querying the entire database","Get quick answers to domain-specific questions (e.g., 'What are the latest approaches to protein folding?') without reading full papers"],"best_for":["Students seeking quick research overviews before diving into full papers","Non-specialists needing accessible explanations of technical topics","Researchers exploring adjacent fields and needing rapid background synthesis"],"limitations":["Synthesis quality depends on LLM hallucination rate; may generate plausible-sounding but incorrect citations or misrepresent paper findings","No explicit fact-checking or confidence scoring visible; users cannot easily verify if synthesized claims are supported by cited papers","Conversation context window likely limited (typical LLM context: 4K-128K tokens); very long research threads may lose earlier context","Synthesis may oversimplify nuanced or contradictory findings across papers, presenting false consensus"],"requires":["Account creation (freemium tier available)","Internet connection for real-time paper retrieval and LLM inference","No API key required beyond platform authentication"],"input_types":["natural language research questions (e.g., 'How do transformer models compare to RNNs for sequence modeling?')","follow-up clarifications and refinements in conversational format"],"output_types":["natural language synthesis with inline citations (paper titles, authors, years)","links to full papers for deeper reading","structured summaries of key findings across multiple papers"],"categories":["text-generation-language","search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_studyx__cap_2","uri":"capability://text.generation.language.ai.writing.assistance.with.academic.context","name":"ai-writing-assistance-with-academic-context","description":"Provides real-time writing suggestions (grammar, clarity, tone, structure) integrated with academic paper context, allowing users to improve essays while maintaining citations and academic rigor. Likely uses a combination of rule-based grammar checking (similar to Grammarly) and LLM-based style suggestions, with awareness of academic writing conventions. May include plagiarism detection by cross-referencing against the 200M paper corpus and web sources.","intents":["Get grammar and style feedback on essays while writing, without switching to a separate tool","Improve academic writing tone and clarity while preserving citations and technical accuracy","Check for unintentional plagiarism by comparing my writing against academic sources"],"best_for":["Undergraduate students writing essays and research papers","Non-native English speakers seeking grammar and clarity feedback","Students concerned about plagiarism detection and citation accuracy"],"limitations":["Writing assistance quality likely inferior to specialized tools like Grammarly (which has 10+ years of refinement and 1B+ user feedback signals)","Plagiarism detection may have false positives when comparing against 200M papers; common phrases in academic writing may trigger false matches","No explicit support for citation format checking (APA, MLA, Chicago, etc.); users must manually verify citation formatting","Real-time suggestions may add latency (typical LLM inference: 500ms-2s per suggestion) making interactive writing experience slower than local grammar checkers"],"requires":["Account creation (freemium tier available)","Internet connection for real-time LLM inference and plagiarism checking","Text input (minimum ~100 words for meaningful feedback)"],"input_types":["essay or paper text (plain text, likely supports copy-paste or document upload)","optional: citation list for plagiarism checking context"],"output_types":["inline suggestions for grammar, clarity, tone, structure","plagiarism report with matched sources and similarity percentages","overall writing quality score or feedback summary"],"categories":["text-generation-language","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_studyx__cap_3","uri":"capability://automation.workflow.cross.platform.synchronized.learning.workspace","name":"cross-platform-synchronized-learning-workspace","description":"Provides consistent user experience and data synchronization across web, mobile (iOS/Android), and desktop platforms, allowing users to start research on phone, continue on laptop, and access saved papers/notes on tablet without data loss or manual export. Likely uses cloud-based state management with real-time sync (WebSocket or polling-based) and local caching for offline access. Synchronization likely includes saved papers, conversation history, writing drafts, and annotations.","intents":["Start researching on my phone during commute and seamlessly continue on my laptop at home","Access my saved papers and notes across all my devices without manual file management","Work offline on mobile and have changes sync when reconnected"],"best_for":["Students and researchers who frequently switch between devices","Mobile-first learners who prefer phone-based research during commutes","Users in areas with intermittent internet connectivity who need offline capability"],"limitations":["Cross-platform sync introduces data consistency challenges; conflicts may occur if user edits same document on multiple devices simultaneously (no explicit conflict resolution visible)","Offline capability likely limited to cached data; cannot perform new semantic searches or paper retrieval without internet","Mobile app performance may lag desktop version due to smaller screen real estate and processing constraints","Synchronization latency typically 1-5 seconds; real-time collaboration features (if present) may feel sluggish compared to native apps"],"requires":["Account creation with cloud storage backend","Internet connection for initial sync and new data retrieval (offline mode requires prior caching)","Mobile: iOS 13+ or Android 8+","Desktop: modern browser (Chrome, Safari, Firefox) or native app"],"input_types":["user actions across all platforms (searches, paper saves, annotations, writing edits)"],"output_types":["synchronized state across all devices (saved papers, conversation history, drafts, notes)"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_studyx__cap_4","uri":"capability://automation.workflow.freemium.tiered.access.with.usage.limits","name":"freemium-tiered-access-with-usage-limits","description":"Implements a freemium pricing model with free tier offering limited searches/queries per day and premium tier removing limits or adding advanced features. Likely uses API rate limiting and quota management to enforce tier boundaries. Free tier provides sufficient functionality for basic student use cases (e.g., 5-10 searches/day, limited chatbot queries) while premium tier targets power users and institutions. Monetization likely through individual subscriptions and institutional licenses.","intents":["Try the platform risk-free before committing to paid subscription","Use basic features (paper search, writing help) without paying if my usage is light","Upgrade to premium when I need unlimited access for intensive research projects"],"best_for":["Budget-conscious students with light-to-moderate research needs","Researchers evaluating the platform before institutional adoption","Casual learners who need occasional research help but not daily usage"],"limitations":["Free tier usage limits (exact numbers unknown) may frustrate power users; typical freemium limits: 5-10 searches/day, 3-5 chatbot queries/day","Premium pricing unknown; may be prohibitively expensive for students in low-income regions","No clear upgrade path or feature comparison visible; users may not understand what they gain by upgrading","Free tier may have degraded performance (slower search results, lower priority inference) compared to premium, creating artificial friction"],"requires":["Account creation (email or social login)","No payment required for free tier","Valid payment method (credit card) for premium tier"],"input_types":["user tier selection during signup"],"output_types":["access to platform features based on tier","usage statistics and quota remaining"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_studyx__cap_5","uri":"capability://data.processing.analysis.multi.domain.paper.indexing.with.metadata.extraction","name":"multi-domain-paper-indexing-with-metadata-extraction","description":"Ingests and indexes 200M+ academic papers across multiple domains (computer science, biology, physics, chemistry, medicine, social sciences, etc.) with automated metadata extraction including title, authors, abstract, publication date, journal/conference, DOI, and citation count. Likely uses OCR for older papers and structured metadata parsing for modern papers with machine-readable formats. Metadata enables filtering, sorting, and citation graph construction. Indexing pipeline likely runs continuously to incorporate newly published papers.","intents":["Search across all academic domains with a single query rather than using domain-specific databases","Filter papers by publication date, journal quality, or citation count to find high-impact work","Access paper metadata (authors, abstract, DOI) without visiting publisher websites"],"best_for":["Interdisciplinary researchers exploring topics across multiple fields","Students unfamiliar with domain-specific databases (PubMed, arXiv, etc.)","Researchers seeking comprehensive coverage rather than specialized depth"],"limitations":["200M corpus is smaller than Google Scholar (~500M) and may miss niche or very recent papers","Metadata extraction quality varies; older papers or non-English papers may have incomplete or inaccurate metadata","No explicit coverage information visible; unclear which journals/conferences are fully indexed vs. partially indexed","Indexing lag time (typically 3-6 months) means very recent preprints may not be searchable","No support for full-text search; searches limited to metadata (title, abstract, authors) rather than paper body"],"requires":["Internet connection for search","Account creation (freemium tier available)"],"input_types":["search query (metadata-based)","optional filters: publication date range, domain/field, journal name"],"output_types":["ranked list of papers with extracted metadata","citation count and impact metrics","links to paper PDFs or abstract pages"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_studyx__cap_6","uri":"capability://search.retrieval.citation.graph.traversal.for.related.work.discovery","name":"citation-graph-traversal-for-related-work-discovery","description":"Constructs and traverses a citation graph where nodes are papers and edges represent citations, enabling discovery of related work by following citation chains. When user views a paper, system displays papers that cite it (forward citations) and papers it cites (backward citations), allowing exploration of research lineage. Likely uses citation metadata extraction from paper PDFs and structured citation formats (BibTeX, RIS) to build the graph. Graph traversal enables finding seminal papers, tracking research evolution, and discovering adjacent work.","intents":["Find papers that cite a given paper to see how research has evolved since publication","Discover foundational papers by following backward citations from a recent paper","Explore related work in adjacent areas by traversing citation paths"],"best_for":["Researchers conducting comprehensive literature reviews","Graduate students exploring research lineage and foundational work","Interdisciplinary researchers discovering adjacent fields through citation paths"],"limitations":["Citation graph quality depends on metadata extraction accuracy; missing or incorrect citations create gaps in graph","Forward citations (papers citing a given paper) may be incomplete if citing papers are not in the 200M corpus","Citation graph traversal can be overwhelming; no guidance on which citation paths are most relevant or high-impact","No temporal filtering; cannot easily see how citations have evolved over time or identify citation trends","Self-citations and citation cartels may inflate importance of certain papers"],"requires":["Paper must be in the 200M corpus to have citation graph data","Internet connection for graph traversal","Account creation (freemium tier available)"],"input_types":["paper DOI, title, or author name to initiate graph traversal"],"output_types":["list of citing papers (forward citations)","list of cited papers (backward citations)","visual citation graph (if UI supports it) showing relationship between papers"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_studyx__cap_7","uri":"capability://memory.knowledge.conversational.context.persistence.across.sessions","name":"conversational-context-persistence-across-sessions","description":"Maintains conversation history and context across user sessions, allowing users to resume research threads days or weeks later without losing prior questions, answers, and citations. Likely stores conversation transcripts in cloud database with user-specific access controls. Context persistence enables users to reference earlier findings, build on prior synthesis, and maintain research continuity. May include conversation search to find prior discussions on related topics.","intents":["Resume a research project after a week without re-asking the same questions or losing prior findings","Search my prior conversations to find earlier research on a related topic","Build iteratively on prior synthesis without starting from scratch each session"],"best_for":["Long-term research projects spanning weeks or months","Students managing multiple research topics simultaneously","Researchers who need to reference prior findings without manual note-taking"],"limitations":["Conversation storage increases privacy concerns; users must trust platform with sensitive research data","No explicit privacy controls visible; unclear if conversations are encrypted, anonymized, or used for model training","Conversation search likely limited to metadata (date, topic keywords) rather than semantic search across conversation content","Very long conversation histories (100+ turns) may become unwieldy; no explicit conversation organization or tagging visible","Context window limitations mean very old conversations may be truncated or unavailable for LLM synthesis"],"requires":["Account creation with cloud storage backend","Internet connection for conversation retrieval","Acceptance of data storage and privacy terms"],"input_types":["user research questions and follow-ups (stored as conversation transcript)"],"output_types":["conversation history with prior questions, answers, and citations","search results for prior conversations on related topics"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":38,"verified":false,"data_access_risk":"high","permissions":["Internet connection for real-time search","Account creation (freemium tier available)","No specific API key or authentication beyond platform login","Internet connection for real-time paper retrieval and LLM inference","No API key required beyond platform authentication","Internet connection for real-time LLM inference and plagiarism checking","Text input (minimum ~100 words for meaningful feedback)","Account creation with cloud storage backend","Internet connection for initial sync and new data retrieval (offline mode requires prior caching)","Mobile: iOS 13+ or Android 8+"],"failure_modes":["200M corpus may have incomplete coverage of recent papers (lag time between publication and indexing typically 3-6 months)","Semantic search quality depends on embedding model quality; may miss papers using non-standard terminology","No advanced filtering by publication date, journal impact factor, or citation count visible in product description","Cannot guarantee full-text access to papers; many results likely point to paywalled content requiring institutional access","Synthesis quality depends on LLM hallucination rate; may generate plausible-sounding but incorrect citations or misrepresent paper findings","No explicit fact-checking or confidence scoring visible; users cannot easily verify if synthesized claims are supported by cited papers","Conversation context window likely limited (typical LLM context: 4K-128K tokens); very long research threads may lose earlier context","Synthesis may oversimplify nuanced or contradictory findings across papers, presenting false consensus","Writing assistance quality likely inferior to specialized tools like Grammarly (which has 10+ years of refinement and 1B+ user feedback signals)","Plagiarism detection may have false positives when comparing against 200M papers; common phrases in academic writing may trigger false matches","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.2833333333333333,"quality":0.63,"ecosystem":0.25,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:33.648Z","last_scraped_at":"2026-04-05T13:23:42.562Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=studyx","compare_url":"https://unfragile.ai/compare?artifact=studyx"}},"signature":"/rZllv5ZwMPXK7mOKJiPubShmFViNuMwKNNQ5gmDz8/mqDirARFeE0FsJib+Ihmg1Ao/Wi3CvDCSZTtbvz6jCw==","signedAt":"2026-06-20T15:14:08.208Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/studyx","artifact":"https://unfragile.ai/studyx","verify":"https://unfragile.ai/api/v1/verify?slug=studyx","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}