philgear/pocketgull-circular-posology-1b

PocketGull Circular Posology & Planetary Health Engine

Organization: PocketGull LLC (Oregon Registry: 258869891)
Informatics Lead: Phillip Gear (CMS NPI: 1487569752 | ORCID: 0009-0008-1372-5381)
Base Foundation Model: google/gemma-3-1b-it
Discipline: FDA SLEP Extended Stability, SIRUM Redistribution, Aquatic Ecotoxicity, and Anthroponics
Open Science Provenance: Zenodo DOI 10.5281/zenodo.20647514

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📌 Overview

Grounds medication lifecycle in planetary health economics and circular posology. Evaluates FDA Shelf Life Extension Program (SLEP) stability for solid oral tablets beyond labeled dates, gates SIRUM charity repository redistribution for sealed blisters, audits critical aquatic ecotoxicity (synthetic estrogens, fluoroquinolones, macrolides) with strict no-flush directives, and models liquid gold anthroponic nitrogen/phosphorus closed loops.

This LoRA adapter was fine-tuned using Direct Preference Optimization (DPO) on domain-specific clinical datasets conforming strictly to HIPAA §164.514 Safe Harbor de-identification standards.

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🚀 Quickstart Inference (Transformers & PEFT)

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel

base_model_id = "google/gemma-3-1b-it"
adapter_id = "pocketgull-llc/pocketgull-circular-posology-1b"

tokenizer = AutoTokenizer.from_pretrained(base_model_id)
base_model = AutoModelForCausalLM.from_pretrained(
    base_model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto"
)
model = PeftModel.from_pretrained(base_model, adapter_id)

prompt = "Patient presents with palpitations taking St. John's Wort alongside Warfarin. Evaluate CYP450 metabolism."
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")

with torch.no_grad():
    outputs = model.generate(**inputs, max_new_tokens=256, temperature=0.2)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

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🔒 HIPAA & Regulatory Compliance

• Zero-PHI Retention: Designed for local edge computation and private Google Cloud Vertex AI deployment.
• FDA 520(o) Non-Device CDS: Supportive evidence-grounded tool intended to assist licensed healthcare providers.

📖 Citation

@software{pocketgull_clinical_2026,
  author = {Gear, Phillip},
  title = {Pocket-Gull: Living Medical Intelligence Engine & Open Clinical Science Suite},
  publisher = {Zenodo},
  version = {1.25.0},
  year = {2026},
  doi = {10.5281/zenodo.20647514},
  url = {https://pocketgull.app}
}