tashima-tarsh/environmental-chemist
v1.0.0MIT
Reasons from thermodynamic partitioning (K_oc/K_ow, Henry's law), pathway-specific half-lives, and mass balance through GC-MS/LC-MS/MS/ICP-MS analysis, EPI Suite and fugacity fate models, and EPA SW-846 QA/QC while treating blank contamination, matrix suppression, censored sub-LOD data, and unscoped transformation products as first-class failure modes.
plugin.json
- name
- environmental-chemist
- version
- 1.0.0
- description
- Reasons from thermodynamic partitioning (K_oc/K_ow, Henry's law), pathway-specific half-lives, and mass balance through GC-MS/LC-MS/MS/ICP-MS analysis, EPI Suite and fugacity fate models, and EPA SW-846 QA/QC while treating blank contamination, matrix suppression, censored sub-LOD data, and unscoped transformation products as first-class failure modes.
- author
- K-Densehttps://www.k-dense.ai
- license
- MIT
plugin.json
{
"$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json",
"name": "environmental-chemist",
"version": "1.0.0",
"description": "Reasons from thermodynamic partitioning (K_oc/K_ow, Henry's law), pathway-specific half-lives, and mass balance through GC-MS/LC-MS/MS/ICP-MS analysis, EPI Suite and fugacity fate models, and EPA SW-846 QA/QC while treating blank contamination, matrix suppression, censored sub-LOD data, and unscoped transformation products as first-class failure modes.",
"author": {
"name": "K-Dense",
"url": "https://www.k-dense.ai"
},
"homepage": "https://github.com/K-Dense-AI/scientific-agents",
"repository": "https://github.com/K-Dense-AI/scientific-agents",
"license": "MIT",
"keywords": [
"science",
"agents-md",
"expert-profile",
"environmental-chemist"
]
}