Citation and Traceability for Rehabilitation Equipment

Data Characteristics

Regulatory and standard documents for rehabilitation equipment originate from national medical product administrations, industry associations, and internal quality management systems. These documents are typically in PDF, Word, or scanned image formats. Content includes product registration certificates, technical requirements, manufacturing specifications, clinical trial reports, risk management files, and user manuals. Update frequency is relatively low, primarily occurring with policy adjustments or product iterations. Document structures are complex, containing extensive specialized terminology, diagrams, flowcharts, and tables. Fields include device model, registration number, production license number, scope of application, contraindications, technical parameters (e.g., power, frequency, treatment modes), safety warnings, and maintenance requirements. Units involve voltage (V), current (A), frequency (Hz), time (min), and distance (cm).

Constraints Imposed by These Characteristics on Citation and Traceability

The complexity and specialized nature of rehabilitation equipment regulatory documents demand highly precise citation and traceability. Numerous diagrams and tables within documents directly affect text extraction accuracy, potentially leading to fragmented citations. The low update frequency necessitates regular manual verification of knowledge base content to ensure the validity of cited regulations and standards. Multiple data sources require clear differentiation between national standards, industry norms, and internal company regulations during citation to avoid confusion. The precision of technical parameters and units requires citations to accurately present values and measurement units, preventing misinterpretation. Additionally, scanned documents may have higher OCR error rates, directly impacting subsequent chunking and retrieval, and consequently, citation accuracy.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`Chunk size`	`500 characters`	Balances semantic completeness with recall efficiency, preventing long paragraphs from diluting key information.
`Chunk Overlap Length`	`50 characters`	Ensures contextual continuity, reducing semantic breaks caused by chunking.
`Recall count`	`Top 8 entries`	Rehabilitation equipment regulations are complex, requiring more context to support precise citations.
`Similarity threshold`	`0.75`	Guarantees the professionalism and relevance of recalled content, filtering out low-relevance noise.
`Rerank result count`	`Top 4 entries`	Refines the most relevant and non-redundant citations through reranking, building upon a high recall count.
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Prevents parsing failures when processing large PDFs or scanned documents.

Three Common Mistakes

AI responses show garbled citation numbers due to incorrect frontend rendering logic or non-standard cite_id format from the backend.
Citations are provided for questions not present in the knowledge base because the Similarity threshold is set too low, leading to the recall and citation of irrelevant content.
The conversation request interface does not return the cite_id field because the backend enable_citation parameter is not set to true or the request parameters do not explicitly ask for citation information.

How to Verify Correct Configuration

Ask specific questions about rehabilitation equipment technical parameters. Check if the numerical values and units in the AI's cited response match the original Product technical requirements document.
Upload a Clinical Trial Report containing complex diagrams and tables. Ask questions about the data and verify if the AI's cited source points to the precise page number where the diagram or table is located.
Randomly select 5 Quality Management System Document. Ask about the processes or specifications described within them. Check if the Document Name and page number in the AI's cited response are accurate.
Simulate questions about critical safety information, such as rehabilitation equipment contraindications. Confirm that the AI's cited content is complete and comprehensive. Trace back to the original User Manual by clicking the citation link.

The values provided are common starting points and should be measured against your own samples.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-21.