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Trial Randomization Stratum Label

Qualify an explicit randomization stratum code by source without assigning trial participants.

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Description

Qualify an explicit randomization stratum code by source.

Trial records distinguish protocol labels, participant events, supply balances and cutoff policies. An inclusive cutoff differs from an exclusive one, and a drug-accountability balance does not establish adherence or a suitable dose. Supplied consent and observation states are not independently verified by a local calculation.

Qualify an explicit randomization stratum code by source.

When to use this tool

Use Trial Randomization Stratum Label when you already have trialId, stratumCode, codeSource and need to qualify an explicit randomization stratum code by source.

How to use the tool and how it works

  1. Enter trialId, stratumCode, codeSource. Use the units and conventions below.
  2. Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
  3. Read token. Use the output convention below.

Enter trialId, stratumCode, codeSource using the field constraints below. Encode these values, in exactly that order, as a JSON array and return the serialized array as text in token. String values are preserved without trimming or external terminology lookup.1

Input fieldMeaning and unitsAccepted input
trialIdTrial IdRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 8192.
stratumCodeStratum CodeRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 8192.
codeSourceCode SourceRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 8192.
Output fieldInterpretationReturned shape
tokenTokenRequired. Text; maximum UTF-16 length 8192.
json
{
  "input": {
    "trialId": "TR17",
    "stratumCode": "S2",
    "codeSource": "Protocol v2"
  },
  "output": {
    "token": "[\"TR17\",\"S2\",\"Protocol v2\"]"
  }
}

Limitations and assumptions

  • The result records supplied values without assigning trial participants. Sources and asserted relationships are not independently authenticated.
  • Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.

Alternative or Complementary methods

Check the controlled protocol, source records, accountability logs and applicable oversight requirements. Use the full trial workflow and analysis for participant or study decisions; local date comparisons and labels do not determine safety, eligibility or treatment.

References

  1. Calculation and input contract: clinical-trials/trial-randomization-stratum-label — tool.io

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