# Detailed Evaluation: VOICE - CLAUDECODE_AGENT_CORE

Evaluated: 2026-04-10T14:06:47.233360
File: `data/d4d_concatenated/claudecode_agent_core/VOICE_d4d_core.yaml`

## Overall Scores

- **Rubric10**: 40.0/50 (80.0%)
- **Rubric20**: 71.0/88 (80.7%)

## Rubric10 Element Scores

| ID | Element | Score | Details |
|----|---------|-------|---------|
| 1 | Dataset Discovery and Identification | 4/5 | 4/5 sub-elements present |
| 2 | Dataset Access and Retrieval | 5/5 | 5/5 sub-elements present |
| 3 | Data Reuse and Interoperability | 2/5 | 2/5 sub-elements present |
| 4 | Ethical Use and Privacy Safeguards | 3/5 | 3/5 sub-elements present |
| 5 | Data Composition and Structure | 5/5 | 5/5 sub-elements present |
| 6 | Data Provenance and Version Tracking | 5/5 | 5/5 sub-elements present |
| 7 | Scientific Motivation and Funding Transparency | 5/5 | 5/5 sub-elements present |
| 8 | Technical Transparency (Data Collection and Processing) | 4/5 | 4/5 sub-elements present |
| 9 | Dataset Evaluation and Limitations Disclosure | 4/5 | 4/5 sub-elements present |
| 10 | Cross-Platform and Community Integration | 3/5 | 3/5 sub-elements present |

### Rubric10 Sub-Element Details


#### 1. Dataset Discovery and Identification

Can a user or system discover and uniquely identify this dataset?

- ✅ **Persistent Identifier (DOI, RRID, or URI)**
  - Found: doi: 10.13026/37yb-1t42
- ✅ **Dataset Title and Description Completeness**
  - Found: title: Bridge2AI-Voice - An ethically-sourced, diverse voice dataset linked to health information
- ✅ **Keywords or Tags for Searchability**
  - Found: keywords: list (non-empty)
- ✅ **Landing Page and Resources (page, hierarchical resources)**
  - Found: page: https://docs.b2ai-voice.org
- ❌ **Hierarchical Structure (parent datasets, relationships)**
  - Fields checked: parent_datasets, related_datasets

#### 2. Dataset Access and Retrieval

Can the dataset and its associated resources be located, accessed, and downloaded?

- ✅ **Access Policy and IP Restrictions Defined**
  - Found: license_and_use_terms: dict (non-empty)
- ✅ **Regulatory Compliance and Confidentiality Classification**
  - Found: regulatory_restrictions: dict (non-empty)
- ✅ **Download URL or Platform Link Available**
  - Found: download_url: https://physionet.org/content/b2ai-voice/
- ✅ **Distribution Formats and File Types Specified**
  - Found: distribution_formats: list (non-empty)
- ✅ **Related Datasets and External Resources Linked**
  - Found: external_resources: list (non-empty)

#### 3. Data Reuse and Interoperability

Is sufficient information provided to reuse and integrate the dataset with others?
Note: Evaluate whether the dataset is designed for integration with similar datasets, including: common identifiers for cross-dataset linking, standardized formats for data harmonization, and documented integration procedures.


- ✅ **License Terms Allow Reuse**
  - Found: license_and_use_terms: dict (non-empty)
- ❌ **Data Formats Are Standardized (encoding, format)**
  - Fields checked: format, encoding
- ❌ **Schema or Ontology Conformance Stated**
  - Fields checked: conforms_to, conforms_to_schema
- ❌ **Variable Metadata with Identifiers Defined**
  - Fields checked: variables
- ✅ **Use Guidance Provided (intended, prohibited uses)**
  - Found: intended_uses: list (non-empty)

#### 4. Ethical Use and Privacy Safeguards

Does the dataset provide clear information about consent, privacy, and ethical oversight?

- ✅ **IRB or Ethics Review and Data Protection Impact**
  - Found: ethical_reviews: list (non-empty)
- ✅ **Deidentification Method Described**
  - Found: is_deidentified: dict (non-empty)
- ❌ **Privacy Protections and Re-identification Risk Assessment**
  - Fields checked: participant_privacy, reidentification_risk
- ✅ **Informed Consent Obtained from Participants**
  - Found: informed_consent: list (non-empty)
- ❌ **Vulnerable Populations and Compensation Documented**
  - Fields checked: vulnerable_populations, participant_compensation

#### 5. Data Composition and Structure

Can the dataset's structure, modality, and population be understood from metadata?

- ✅ **Cohort or Subpopulations Characteristics Described**
  - Found: subpopulations: list (non-empty)
- ✅ **Number of Instances or Samples Reported**
  - Found: instances: list (non-empty)
- ✅ **Variable-Level Metadata, Tabular Flag, and Data Splits**
  - Found: is_tabular: False
- ✅ **Data Topics or Conditions Represented**
  - Found: instances: list (non-empty)
- ✅ **Data Quality, Anomalies, and Missing Data Documented**
  - Found: sampling_strategies: list (non-empty)

#### 6. Data Provenance and Version Tracking

Can a user determine dataset versions, update history, and provenance?

- ✅ **Dataset Version Number Provided**
  - Found: version: 3.0.0
- ✅ **Version Access Methods Documented**
  - Found: version_access: dict (non-empty)
- ✅ **Change Descriptions and Errata Provided**
  - Found: updates: dict (non-empty)
- ✅ **Update Schedule or Frequency Indicated**
  - Found: updates: dict (non-empty)
- ✅ **Provenance, Source Derivation, and Raw Data Sources**
  - Found: raw_data_sources: list (non-empty)

#### 7. Scientific Motivation and Funding Transparency

Does the metadata clearly state why the dataset exists and who funded it?

- ✅ **Motivation or Purpose for Dataset Creation**
  - Found: purposes: list (non-empty)
- ✅ **Primary Research Objectives or Tasks**
  - Found: tasks: list (non-empty)
- ✅ **Funding Sources and Mechanisms Listed**
  - Found: funders: list (non-empty)
- ✅ **Grant IDs or Award Numbers Present**
  - Found: funders: list (non-empty)
- ✅ **Creators and Acknowledgements Documented**
  - Found: creators: list (non-empty)

#### 8. Technical Transparency (Data Collection and Processing)

Can data collection and processing steps be replicated or understood?
Note: Preprocessing and collection metadata may be represented as structured text descriptions OR as machine-readable provenance graphs (e.g., W3C PROV-O, workflow graphs). Evaluation should check for: (1) structured text descriptions OR (2) graph representations with entity-activity-agent relationships. Both formats are acceptable.


- ✅ **Collection Mechanisms and Settings Described**
  - Found: collection_mechanisms: list (non-empty)
- ✅ **Data Acquisition Methods Listed**
  - Found: acquisition_methods: list (non-empty)
- ✅ **Preprocessing, Cleaning, Labeling, and Annotation Quality**
  - Found: preprocessing_strategies: list (non-empty)
- ❌ **Software and Tools Documented**
  - Fields checked: software_and_tools
- ✅ **External Standards, Resources, and Imputation Protocols**
  - Found: external_resources: list (non-empty)

#### 9. Dataset Evaluation and Limitations Disclosure

Does the metadata communicate known risks, biases, or dataset limitations?

- ✅ **Known Limitations Documented**
  - Found: known_limitations: list (non-empty)
- ✅ **Biases Categorized Using Standard Taxonomy (RAI-aligned)**
  - Found: known_biases: list (non-empty)
- ❌ **Data Anomalies and Quality Issues Noted**
  - Fields checked: anomalies
- ✅ **Sensitive Content and Warnings Provided**
  - Found: sensitive_elements: list (non-empty)
- ✅ **Ethical Review and Social Impact Analysis**
  - Found: ethical_reviews: list (non-empty)

#### 10. Cross-Platform and Community Integration

Does the dataset connect to wider data ecosystems, repositories, or standards?
Note: For Bridge2AI datasets, citation metadata is mandatory and should include: (1) formatted citation string, (2) DOI, and (3) citation instructions. Hosting platform identification should specify the publisher or repository (e.g., PhysioNet, Dataverse, institutional repositories).


- ✅ **Dataset Published on a Recognized Platform**
  - Found: publisher: Bridge2AI-Voice Consortium, University of South Florida
- ✅ **Citation and DOI for Cross-referencing**
  - Found: doi: 10.13026/37yb-1t42
- ❌ **Community Standards or Schema Conformance**
  - Fields checked: conforms_to
- ✅ **Outreach Materials and Documentation Links**
  - Found: external_resources: list (non-empty)
- ❌ **Related Datasets with Typed Relationships**
  - Fields checked: related_datasets

## Rubric20 Question Scores


### Structural Completeness

| ID | Question | Score | Status |
|----|----------|-------|--------|
| 1 | Field Completeness | 4.0/5 | ✅ |
| 2 | Entry Length Adequacy | 4.0/5 | ✅ |
| 3 | Keyword Diversity | 4.0/5 | ✅ |
| 4 | File Enumeration and Type Variety | 4.0/5 | ✅ |
| 5 | Data File Size Availability | Pass | ✅ |

### Metadata Quality & Content

| ID | Question | Score | Status |
|----|----------|-------|--------|
| 6 | Dataset Identification Metadata | Pass | ✅ |
| 7 | Funding and Acknowledgements Completeness | 4.0/5 | ✅ |
| 8 | Ethical and Privacy Declarations | 4.0/5 | ✅ |
| 9 | Access Requirements and Governance Documentation | 4.0/5 | ✅ |
| 10 | Interoperability, Standardization, and Cross-Platform Integration | 4.0/5 | ✅ |

### Technical Documentation

| ID | Question | Score | Status |
|----|----------|-------|--------|
| 11 | Tool and Software Transparency | 4.0/5 | ✅ |
| 12 | Collection Protocol Clarity | 4.0/5 | ✅ |
| 13 | Version History, Maintenance, and Sustainability | 4.0/5 | ✅ |
| 14 | Associated Publications | 4.0/5 | ✅ |
| 15 | Human Subject Representation | 4.0/5 | ✅ |

### FAIRness & Accessibility

| ID | Question | Score | Status |
|----|----------|-------|--------|
| 16 | Findability (Persistent Links) | Pass | ✅ |
| 17 | Accessibility (Access Mechanism) | 4.0/5 | ✅ |
| 18 | Reusability, Use Guidance, and Social Impact | 4.0/5 | ✅ |
| 19 | Data Integrity, Provenance Graph, and Quality | 4.0/5 | ✅ |
| 20 | Bias Documentation and Responsible AI Alignment | 4.0/5 | ✅ |