| --- |
| language: |
| - en |
| license: mit |
| pretty_name: Pharma Context Optimization & Response Enhancement Forecasting v0.1 |
| dataset_name: pharma-context-optimization-response-enhancement-forecasting-v0.1 |
| tags: |
| - clarusc64 |
| - pharma |
| - placebo |
| - context |
| - clinical-trials |
| - response-forecasting |
| 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 forecast how contextual adjustments |
| alter treatment response and stability. |
|
|
| It treats context as a controllable amplifier |
| of therapeutic coherence. |
|
|
| Required outputs |
|
|
| - optimal_context_shift_set |
| - projected_response_gain |
| - placebo_amplification_ceiling |
| - nocebo_suppression_gain |
| - context_sensitivity_index |
| - forecast_confidence |
|
|
| Use case |
|
|
| Third layer of the Placebo/Nocebo Response Disentanglement Matrix. |
|
|
| Enables: |
| - context-aware trial design |
| - response amplification without dose escalation |
| - nocebo suppression strategies |
|
|
