---
language:
  - en
license: mit
pretty_name: Pharma Pharmacological vs Contextual Signal Separation v0.1
dataset_name: pharma-pharmacological-vs-contextual-signal-separation-v0.1
tags:
  - clarusc64
  - pharma
  - placebo
  - nocebo
  - clinical-trials
  - signal-separation
task_categories:
  - tabular-regression
  - tabular-classification
size_categories:
  - n<1K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train.csv
      - split: test
        path: data/test.csv
---

What this dataset tests

Whether a system can separate pharmacological effect from contextual modulation  
in placebo-controlled clinical trial settings.

It treats context as a learnable component of the outcome manifold.

Required outputs

- pure_pharmacological_effect  
- contextual_amplification_factor  
- nocebo_risk_index  
- signal_separation_confidence  
- effect_stability_score  

Use case

Second layer of the Placebo/Nocebo Response Disentanglement Matrix.

Improves efficacy estimation by preventing:
- placebo lift being counted as drug effect  
- nocebo effects being misread as toxicity  
- unstable effects being over-trusted