Addiction Withdrawal Level-of-Care Constraint Evaluation Dataset

#clinical constraint verification #level-of-care appropriateness assessment #clinical reasoning evaluation #addiction withdrawal management #level-of-care assessment #clinical decision support

5000
0.3GB
JSON
CATL
MOBIUSI INC

Updated:2026-10-19

AI Analysis & Value Prop

This evaluation dataset presents structured cases involving addiction withdrawal, including risk conditions, care-resource constraints, and a proposed level-of-care recommendation to validate. Each case includes a reference judgment indicating whether the recommendation satisfies the stated constraints and identifying potential conflicts, supporting evaluation of constraint reasoning and recommendation validation in addiction psychiatry. The dataset is intended for research and model evaluation, not as a substitute for professional clinical judgment.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
case_input	object	Structured case information and the proposed level-of-care recommendation to be evaluated.
evaluation_summary	string	Concise summary of the benchmark case and its constraint-validation outcome.
reference_annotation	object	Benchmark judgment on whether the proposed recommendation satisfies the case constraints, including the rationale.
constraint_validation	object	Normalized validation result derived from the case input and reference annotation.

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

Frequently Asked Questions

What does the evaluation dataset contain?: Each sample includes structured withdrawal case information, risk conditions, care-resource constraints, and a proposed level-of-care recommendation. Reference judgments and normalized validation results help assess whether a recommendation meets the case constraints and identify conflicts.

Which capabilities can this dataset evaluate?: It can support evaluation of constraint reasoning, level-of-care recommendation validation, and conflict detection in withdrawal-care scenarios, as well as research on related evaluation workflows and benchmarks.

Is the dataset intended for clinical decision-making?: The dataset is intended for research and model evaluation. It does not provide diagnosis or treatment advice and should not be used on its own to make clinical decisions. Actual care decisions should be made by qualified professionals using the full clinical context and applicable standards.

How can I obtain the data and verify its license?: Check the dataset product page or the provider's published channels for access instructions, available formats, and license terms. Before use, review the permitted scope, redistribution restrictions, and applicable privacy and compliance requirements.

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Cite this Work

@dataset{Mobiusi2026,
  title={Addiction Withdrawal Level-of-Care Constraint Evaluation Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/365b49c45f2d8063df3605c0095b595a},
  urldate={2026-10-12},
  keywords={addiction withdrawal evaluation dataset,withdrawal level of care,addiction psychiatry data,constraint verification dataset,clinical constraint reasoning,care recommendation evaluation,withdrawal management model evaluation,structured clinical cases},
  version={1.0}
}

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