Data Characteristics in this Category
Quality documents in biomedical clinical trial pre-screening primarily include investigator brochures, clinical trial protocols, ethics committee approval letters, informed consent form templates, and case report forms. These documents are typically in PDF, Word, or scanned image formats. Data sources include sponsors, clinical research organizations, and central laboratories. The update frequency is relatively low, usually occurring before trial initiation or when protocol amendments or safety information updates happen during the trial. Document structures are rigorous, containing extensive specialized terminology, medical abbreviations, and regulatory clauses. Fields (e.g., drug name, dosage, subject inclusion/exclusion criteria, adverse event grades) are highly standardized, and units (e.g., mg, mL, IU, MCI) are precise and standardized.
Constraints Imposed by these Characteristics on "Reference Sourcing and Traceability"
The specialized and rigorous nature of quality documents demands that references precisely point to specific paragraphs in original documents, avoiding generalization or misleading information. Low update frequency makes historical version management crucial, requiring assurance that the referenced version is currently effective. The accuracy of specialized fields and units in documents determines whether the RAG (Retrieval Augmented Generation) system can correctly understand and restate key information when generating responses. For scanned documents, OCR (Optical Character Recognition) accuracy directly impacts text extraction and subsequent retrieval effectiveness. Furthermore, regulatory compliance requires the referencing process to be auditable, with clear traceability to the original source to meet compliance requirements.
Configuration Settings
| Configuration Item | Recommended Value | Rationale for this Value |
|---|---|---|
chunk_size | 500-800 characters | Ensures individual segments contain sufficient context while avoiding information redundancy, which aids precise matching of specialized terminology. |
overlap_size | 100-150 characters | Guarantees contextual continuity between segments, reducing semantic breaks caused by segment boundaries. |
retrieval_top_k | top 5 | Controls the number of retrieval results while maintaining recall rate, reducing computational cost for subsequent processing. |
similarity_threshold | Calibrated by actual measurement | Ensures retrieved segments are highly relevant to the query, excluding low-quality or irrelevant information to prevent incorrect references. |
rerank_top_n | top 3 | Re-ranks initial retrieval results to further improve the ranking of the most relevant information, enhancing reference quality. |
document_versioning_enabled | True | Ensures that in multi-version documents, the latest or specified effective version is always referenced. |
Three Common Mistakes
- When generating a response, the cited original content does not match the semantic meaning of the response. This occurs because the chunk granularity is too large, leading to retrieved chunks containing irrelevant information.
- The system claims no relevant references were found, but a manual search by the user reveals the information exists in the document. This might be due to OCR errors or a failure to effectively extract key entities during document pre-processing.
- Knowledge base reference display was turned off in the conversation, but the system still responded based on knowledge base content. This prevents users from verifying information sources because only the front-end display was disabled, while the back-end RAG process continued to execute.
How to Confirm Proper Configuration
- For typical queries, check if the cited original snippets in the response are highly relevant and accurate to the generated content.
- Randomly select multiple quality documents in different formats to verify if the system can correctly identify and extract key fields and units.
- Simulate document update scenarios, query old version information, and confirm if the system can correctly reference or indicate version invalidation.
The values provided are common starting points and should be measured against the reader's 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.