metadata
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