Model Cards

Model cards for temporalcv validation components, following the Mitchell et al. (2019) framework adapted for ML infrastructure.

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Overview

Model cards provide transparent documentation of component behavior, assumptions, and limitations. Each card includes:

• Component Details: Version, module, license, knowledge tier

• Intended Use: Primary use cases and out-of-scope applications

• Parameters: Complete parameter reference with knowledge tier tags

• Assumptions: What must hold for correct behavior

• Limitations: Known constraints and common misconfigurations

• References: Academic sources tagged by confidence tier

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Available Model Cards

Component	Type	Card
WalkForwardCV	Cross-validator	walk_forward_cv.md
gate_signal_verification	Validation gate	gate_signal_verification.md

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Knowledge Tier System

All claims are tagged with confidence levels:

Tier	Meaning	Example
[T1]	Academically validated	DM test (Diebold & Mariano 1995)
[T2]	Empirical finding	Block permutation default
[T3]	Assumption/heuristic	α=0.05 significance level

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Using Model Cards

Before Deployment

1. Read the Intended Use section to verify your use case is supported

2. Check Assumptions against your data and pipeline

3. Review Limitations for known constraints

During Development

1. Use Parameters table as a quick reference

2. Check Common Misconfigurations to avoid pitfalls

3. Follow Examples for correct usage patterns

For Documentation

1. Cite References in publications

2. Use Knowledge Tier tags for claim confidence

3. Note Limitations in methodology sections

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Contributing

To add a new model card:

1. Copy the template structure from existing cards

2. Fill in all sections with accurate information

3. Tag all claims with appropriate knowledge tiers

4. Add academic references for [T1] claims

5. Document empirical sources for [T2] claims

6. Justify [T3] heuristics explicitly

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Reference

Mitchell, M., Wu, S., Zaldivar, A., Barnes, P., Vasserman, L., Hutchinson, B., Spitzer, E., Raji, I.D., & Gebru, T. (2019). Model Cards for Model Reporting. Proceedings of the Conference on Fairness, Accountability, and Transparency, 220-229.