---
language:
- en
license: mit
task_categories:
- text-classification
tags:
- clarus
- f1
- thermal
- latent-instability
- cross-coupling
size_categories:
- 1K<n<10K
pretty_name: F1 Latent Cross-Coupling Thermal Load Instability v0.1
---

# What this repo does

Detects hidden thermal instability before performance loss appears.

Focus: temperature-driven failure across interacting systems.

# Core variables

- tyre_temp_load  
- brake_temp_load  
- power_unit_heat_load  
- cooling_efficiency  

# Prediction target

`label_thermal_load_instability`

1 → thermal regime will force performance drop  
0 → thermal state remains stable  

# Key idea

Thermal failure is rarely single-source.

It emerges from interaction:

- tyre overheating  
- brake heat transfer  
- power unit load  
- cooling limits  

# Label logic

label = 1 if:

- latent_instability_score ≥ 0.60  
- cross_coupling_intensity ≥ 0.60  
- hidden_state_index ≥ 0.60  
- activation_threshold_distance ≤ 0.35  
- tyre_temp_load ≥ 0.80  
- brake_temp_load ≥ 0.78  
- power_unit_heat_load ≥ 0.75  
- tyre_temp_load > stabilization_buffer  

# Why this matters

Performance loss is often thermal before it is visible.

This dataset detects:

- overheating before lap time drop  
- cooling saturation before failure  
- system interaction before degradation  

# Use cases

- race strategy  
- cooling configuration  
- stint planning  
- simulation  

# Evaluation

Primary:
missed_latent_activation_rate  

Secondary:
false_activation_rate  

# Structural Note

This sits in the latent detection layer.

It detects hidden thermal instability before performance collapse appears.

# Production Deployment

Used for:

- live telemetry augmentation  
- predictive race control  
- simulation pipelines  

# Collaboration

Suitable for:

- F1 teams  
- motorsport analytics  
- simulation groups  

# License

MIT