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Documentation Index

Fetch the complete documentation index at: https://wuweism.com/llms.txt

Use this file to discover all available pages before exploring further.

Wu-Weism can analyze research papers directly. You can attach a PDF to any Causal Chat message — the extracted evidence then grounds the response in the paper’s actual data — or use the dedicated PDF Synthesis tool to cross-analyze up to six papers simultaneously. Both surfaces extract structured numeric evidence, generate governed claims, and record everything in the Claim Ledger.

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Two ways to use PDFs

Attach a single PDF to a Causal Chat message. The PDF’s content is extracted and used to inform the causal response to your question. Best for:
  • Grounding a specific causal question in a paper’s reported data
  • Checking whether a paper’s findings support or contradict a claim
  • Extracting key statistics while also running causal analysis

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Analyzing a single paper in Causal Chat

1

Open a Causal Chat conversation

Navigate to /chat and start a new conversation or continue an existing one.
2

Click the attachment button

Click the paperclip icon (attachment button) in the message input bar. A file picker will open. Select your PDF file.The PDF name will appear as an attachment chip next to the message input. You can attach one PDF per message.
3

Type your question

Write your causal question in the message input as you normally would. The question will be analyzed in the context of the attached paper.
Example question with PDF attached
What causal claims about IL-6 and fibrosis progression does this paper support?
Another example
Does the methodology in this paper meet the identifiability requirements 
for a Rung 2 intervention claim?
4

Read the three-section output

When a PDF is attached, the response follows a structured three-section output contract:
Section 1: All explicit numbers with contextEvery numeric value extracted from the paper, grouped by category:
CategoryExamples
Potential metricsEffect sizes, p-values, confidence intervals, odds ratios
StructuralSample sizes, group counts, time points, dosages
BibliographicPublication year, journal impact factor if present
Citation yearsYears of cited works
Reference indicesReference numbers linked to cited claims
Section 2: Claim-eligible numericsA filtered subset of Section 1 containing only the values that are precise enough and contextually clear enough to anchor a governed claim. Values with ambiguous units, missing context, or contradictory definitions elsewhere in the paper are excluded from this section.
Section 3: Three claims with uncertainty labelsThree governed claims derived from the paper’s evidence. Each claim carries an evidence class label:
Evidence classMeaning
bibliographic/structural onlyThe claim is supported only by citation references or study design information — no direct numeric metrics
mixedThe claim combines structural evidence with some numeric data, but the metrics are indirect or aggregated
metric-bearingThe claim is directly supported by explicit numeric measurements from the paper
Example Section 3 output
[Claim 1 — metric-bearing]
Anti-inflammatory treatment reduced IL-6 levels by 38% (95% CI: 24–51%) 
in the intervention arm vs. control at 12 weeks.
Uncertainty: metric-bearing | Confidence: 0.79

[Claim 2 — mixed]
Fibrosis progression was attenuated in the treatment group, consistent 
with reduced IL-6 signaling, though direct fibrosis measurements were 
not stratified by IL-6 quartile.
Uncertainty: mixed | Confidence: 0.52

[Claim 3 — bibliographic/structural only]
The study design is consistent with prior RCT methodology for cytokine 
intervention trials (citations: [12], [14], [17]).
Uncertainty: bibliographic/structural only | Confidence: 0.41
All three claims are automatically recorded in the Claim Ledger.
Wu-Weism extracts text from PDFs using the document’s text layer. Scanned PDFs — images of printed pages with no embedded text — will have significantly lower extraction quality. Key statistics may be missed, misread, or absent from Sections 1 and 2. If you are working with scanned documents, use OCR software to create a searchable PDF before uploading. Claims derived from scanned PDFs will be labeled with lower confidence scores.

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Using PDF Synthesis for multi-paper analysis

PDF Synthesis is a dedicated research surface at /pdf-synthesis designed for analyzing multiple papers at once.
1

Navigate to /pdf-synthesis

Open PDF Synthesis from the workbench navigation.
2

Upload your PDFs

Drag and drop up to six PDF files into the upload area, or click Select files to use the file picker. Each file appears in the upload queue with its name and size.
3

Optionally specify a research focus

In the Research focus field, enter a brief description of what you are investigating. This helps Wu-Weism weight evidence and frame claims around your specific question rather than the papers’ full scope.
Example research
Effect of anti-inflammatory interventions on IL-6 in patients with 
chronic kidney disease
Providing a research focus consistently improves synthesis quality. Without it, Wu-Weism treats each paper equally and generates claims that reflect the papers’ own framings, which may not align with your specific research question. Even a one-sentence focus statement makes a meaningful difference.
4

Review synthesized output

The synthesis produces:
  • Numeric evidence summary: Aggregated metrics across all papers, including table counts, trusted table counts (tables where headers and data are reliably parsed), and total data point counts per paper.
  • Cross-paper claim comparison: Where multiple papers address the same causal relationship, Wu-Weism surfaces agreement and contradiction.
  • Governed claims set: Claims derived from the full corpus, each attributed to the source paper(s) and labeled with an evidence class.
  • Reconciliation notes: Where papers conflict on effect direction or magnitude, the synthesis explicitly flags the disagreement rather than averaging it away.

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What gets extracted

When Wu-Weism processes a PDF — whether in Causal Chat or PDF Synthesis — it extracts:
Extracted fieldDescription
Numeric evidenceAll numeric values with surrounding context
Table countsNumber of tables identified in the document
Trusted table countsTables where structure is reliably parsed (headers and rows matched)
Data point countsTotal discrete numeric data points extracted
ClaimsCandidate claims derived from evidence
Bibliographic metadataWhere present: authors, year, journal

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Claims and the Claim Ledger

Every claim produced from a PDF analysis — whether in Causal Chat or PDF Synthesis — is automatically recorded in the Claim Ledger with:
  • Source paper name
  • Section of the paper the claim derives from
  • Evidence class label
  • Confidence score
  • Session and timestamp
You can review, annotate, challenge, and export these claims from /claims at any time.

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Limitations

  • Text layer required: PDFs must have an embedded text layer. Scanned-only documents have significantly degraded extraction.
  • Complex table layouts: Multi-level headers, merged cells, and sideways tables may not parse correctly into the trusted table count.
  • Supplementary materials: If supplementary data is in a separate file, upload it as a separate document in PDF Synthesis or attach it in a second Causal Chat message.
  • Non-English papers: Extraction and claim generation quality is highest for English-language documents.

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Next steps