slug: piscescsm
provider: piscesCSM
generated_by: planning/capability-mapping/scripts/classify_capabilities.py
model: claude-opus-5
frame:
- Pharmaceuticals & Life Sciences
min_confidence: 0.7
capability_model:
  source: https://github.com/vincentmakes/turbo-ea-capabilities
  license: CC-BY-4.0
  attribution: Turbo EA Capabilities by Vincent Verdet — Turbo EA, https://github.com/vincentmakes/turbo-ea-capabilities,
    CC BY 4.0
  notice: NOTICE
edge_count: 1
edges:
- tag: Predict
  spec_file: piscescsm-predict-api-openapi.yml
  capability_id: BC-1500
  capability_id_l1: BC-1500
  capability_name: Drug Discovery Management
  confidence: 0.7
  evidence: '''piscesCSM drug-pair cancer sensitivity prediction into research pipelines. Submit a pair
    of small molecules as SMILES strings''; schemas PredictionResult, MolecularDescriptors'
  reason: In-silico prediction of small-molecule (drug-pair) activity across cancer types with molecular
    descriptors is computational drug discovery work. L1 Drug Discovery Management; evidence does not
    pin down whether this is hit discovery, lead optimisation or translational, so no L2. Job-submit/poll
    pattern is only the delivery mechanism.