Evidence and research literacy tool
Noah AI
Noah AI supports direct research questions, scope clarification, and editable evidence. These patient-accessible functions must be distinguished from inferred institutional uses. The evidence does not establish universal absence of recourse or dominant downstream effects.
Published September 8, 2026 as an AI-assisted draft. The public report separates documented facts, agency judgments and unresolved questions.
Summary judgment · 55 out of 100 toward patient-directed
Publicly accessible professional research agent. Evaluate a patient's direct research use separately from hypothetical downstream industry effects. Preserve August 13 baseline 55 and its corrected prior-model history.
Mixed
Noah AI supports direct research questions, scope clarification, and editable evidence. These patient-accessible functions must be distinguished from inferred institutional uses. The evidence does not establish universal absence of recourse or dominant downstream effects.
Patient agency
How this tool changes agency
Citations and downloadable interim analysis can help users challenge framing and conclusions. The baseline's assertion that nothing supports patient action is too absolute: research can support a patient's chosen action without a dedicated appointment or appeal feature.
Direct patient experience, clinical boundaries inside the app, processor terms, research-input use and actual institutional deployments remain unknown.
Patient agency assessment
Who sets and changes the goal?
In direct use, patients can define research goals and constraints and take editable evidence away. Professional market positioning does not erase that authority. Patients affected by another organization's analysis are a different deployment and cannot be assigned a blanket lack of recourse without evidence.
What can the patient understand, question, or do?
Citations and downloadable interim analysis can help users challenge framing and conclusions. The baseline's assertion that nothing supports patient action is too absolute: research can support a patient's chosen action without a dedicated appointment or appeal feature.
Can the patient evaluate the conditions of use?
The policy remains poorly specific about sensitive research inputs and model recipients. Distinguish documented advertising categories from an unsupported claim that health prompts are disclosed to them. Search absence cannot confirm that independent evidence does not exist.
Text findings
Conditions of use
Published controls and their limits
The policy remains poorly specific about sensitive research inputs and model recipients. Distinguish documented advertising categories from an unsupported claim that health prompts are disclosed to them. Search absence cannot confirm that independent evidence does not exist.
What remains unknown?
Not tested or not established
Direct patient experience, clinical boundaries inside the app, processor terms, research-input use and actual institutional deployments remain unknown.
Who evaluated this?
AI-assisted public-source draft
Vendor statements describe published conditions, not independently verified behavior. No clinical, security, accessibility, or legal validation is claimed. Earlier evidence remains dated in the report and history.
Sources checked
Source-specific findings and retrieval limitations are recorded in the full report.
Review provenance
Criteria
CAIHL-derived HugoScore framework and September 7 qualitative review priorities. Draft v1.2 numerical anchors remain unadopted.
Reviewer
AI-assisted public-source reassessment prepared in OpenAI Codex.
AI / model
OpenAI Codex / GPT-6
Human review
Hugo Campos authorized publication of these AI-assisted draft reassessments on September 8, 2026. This does not claim comprehensive human verification of every finding.
Review date
2026-09-08
Limitations
Direct patient experience, clinical boundaries inside the app, processor terms, research-input use and actual institutional deployments remain unknown. No live product use, patient-data upload, account creation, code audit, clinical evaluation, or independent implementation validation.
Review method
Focused public-source reassessment using CAIHL: patient authority, critical capacity, and informed control. Existing evidence plus one focused primary-source pass and at most one targeted follow-up. No live product testing. Numerical scores remain provisional editorial placements, not a new calculation.
AI-assisted draft · Low to medium, primary documents only (AI-assisted draft)