{
  "sample_id": "ilknur_icke_2026-10-06_sfgfp_ribose_mg6975_v1",
  "sample_type": "experimental",
  "reagent_list": {
    "lysate": 5000,
    "template_sfgfp": 2000,
    "base_buffer": 2000,
    "potassium_glutamate": 3325,
    "magnesium_glutamate": 175,
    "amino_acid_mix_17": 1600,
    "hepes_koh": 900,
    "kpo_monobasic_mix": 600,
    "ribose": 1500,
    "nicotinamide": 800,
    "amp": 600,
    "cmp": 425,
    "gmp": 425,
    "ump": 425,
    "nuclease_free_water": 225
  },
  "metadata": {
    "ai_model": "Codex (OpenAI); exact model version not recorded",
    "protein_target": "sfGFP",
    "acknowledgements": "AI-assisted design based on the course sfGFP Ribose reference (sfGFP_R2PC_054), selected from an AI-simulated wet-lab-expert example. No experimental results are claimed.",
    "comments": "Baseline: sfGFP Ribose reference sfGFP_R2PC_054. Reduce the 500 mM magnesium-glutamate stock from 225 to 175 nL; increase water from 175 to 225 nL. All other additions remain unchanged. Including the documented base-buffer contribution, magnesium glutamate decreases from 8.225 to 6.975 mM. Total reaction volume is 20,000 nL, with every transfer in 25 nL increments.\n\nThis is a single-variable test of magnesium sensitivity within the ribose/NMP formulation, not an established optimum. Compare calibrated sfGFP fluorescence with the unchanged reference using matched lysate and assay conditions. Functional output for this candidate has not been measured; no yield or cost-per-gram prediction is claimed.\n\nAI client: Codex (OpenAI). Original user prompt: \"ok now create 3 agents, one undergraduate biology, one graduate level and one practising senior scientist and one very expert level wet lab scientist and have them create their versions of completed homework in independent mode\". The example was subsequently revised against the supplied course inventory. The full authoring and revision prompt record is retained in the homework documentation."
  }
}