Clinical Psychology Risk Triage Constraint Verification Dataset
- Records
- 5000
- Size
- 0.5GB
- Format
- JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-04
This JSON dataset presents case-specific risk factors, protective factors, and recent changes alongside applicable triage and escalation rules, candidate dispositions, and verification outcomes. It supports domain evaluation and quality analysis of models that identify omitted conditions, rule violations, or inconsistencies between a proposed disposition and the case information. It is intended for model evaluation and does not replace professional clinical judgment.
Overview
Dataset Insights
Preview
Sample Examples
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| triage_rules | array | Source rules defining triage thresholds, escalation requirements, or other required actions. |
| risk_alignment | boolean | Indicates whether the candidate disposition is consistent with the documented risk and protective information. |
| required_action | string | The action required by the applicable rules and case information, if any. |
| review_rationale | string | A concise explanation connecting the case information and applicable constraints to the verification outcome. |
| case_risk_profile | object | Source information describing case-specific risk factors, protective factors, and recent changes. |
| overall_assessment | string | Derived outcome indicating whether the candidate disposition satisfies the applicable constraints. |
| constraint_findings | array | Derived findings identifying omitted conditions, constraint violations, or inconsistencies. |
| candidate_disposition | object | The proposed clinical risk disposition to be checked against the case information and applicable rules. |
| constraint_compliance | boolean | Indicates whether the candidate disposition complies with all applicable explicit triage and escalation constraints. |
Trust
Compliance Statement
Authorization Type
Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use
Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization
No PII, no real company names, simulated scenarios follow industry standards
Compliance System
Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs
FAQ
Frequently Asked Questions
- What does the dataset contain?
- The JSON records include case risk and protective information, applicable triage rules, candidate dispositions, and evaluation outcomes such as constraint compliance, risk alignment, and review rationale.
- Which model capabilities can it evaluate?
- It can support evaluation of a model's ability to detect omitted conditions, identify conflicts with triage or escalation rules, and check whether a proposed disposition is consistent with case information. It can also inform quality analysis of related systems.
- Can the dataset be used to make clinical decisions or directly guide care?
- The dataset is intended for domain evaluation and research, not as a standalone basis for diagnosis, risk triage, or clinical disposition. Real-world decisions should follow applicable standards and be made by qualified professionals.
- How can I access the data, and what are the licensing terms?
- Access methods and usage rights are governed by the terms published on the product page or by the data provider. Before use, confirm the license scope, privacy and security requirements, and whether commercial use or redistribution is permitted.
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Cite this Work
@dataset{Mobiusi2026,
title={Clinical Psychology Risk Triage Constraint Verification Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/2d810f93619d725dc7e7d04c54ee8f10?dataset_scene_cate_type=3},
urldate={2026-10-12},
keywords={clinical psychology dataset,risk triage evaluation,constraint verification data,psychological risk disposition,escalation rule checking,clinical model evaluation,risk consistency analysis,JSON evaluation dataset},
version={1.0}
}Using this in research? Please cite us.