Skip to content

Main content

Animal Weight Reference Bias Tool

Compare paired bench mass measurements and supplied references; no animal-health interpretation.

Loading tool…

Description

Return paired weight bias and aggregate-relative bias.

Animal observations distinguish recorded events, classification tokens, count expectations and measurement residuals. A normalized score or supplied activity transition is not a diagnosis or validated behavioral interpretation. Unknown records and incomplete observation windows must remain explicit.

Return paired weight bias and aggregate-relative bias.

When to use this tool

Use Animal Weight Reference Bias when checking the stated animal observation, score, count or time convention.

How to use the tool and how it works

  1. Enter measuredMasses, referenceMasses. Follow any array-alignment requirements below. 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 meanBias, relativeAggregateBias. Use the output convention below.

Return paired weight bias and aggregate-relative bias. Require aligned nonempty nonnegative arrays with positive reference sum; meanBias = (sumMeasured-sumReference)/pairCount, relativeAggregateBias = difference/reference sum.1

Input fieldMeaning and unitsAccepted input
measuredMassesMeasured MassesRequired. Array of finite number; maximum items 256.
referenceMassesReference MassesRequired. Array of finite number; maximum items 256.
Output fieldInterpretationReturned shape
meanBiasMean BiasRequired. Finite number.
relativeAggregateBiasSum of paired errors divided by sum of reference masses; not the mean of individual relative errors.Required. Finite number.
json
{
  "input": {
    "measuredMasses": [
      11,
      21
    ],
    "referenceMasses": [
      10,
      20
    ]
  },
  "output": {
    "meanBias": 1,
    "relativeAggregateBias": 0.06666666666666667
  }
}

Limitations and assumptions

  • This is not the mean of individual relative errors; actual scale calibration, sample identity and uncertainty are not verified.
  • 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.
  • Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.

Alternative or Complementary methods

Inspect the original animal and observation records, use an appropriate statistical model and consult qualified veterinary/husbandry professionals for health or welfare decisions.

References

  1. Calculation and input contract: animal-science/animal-weight-reference-bias — tool.io

Similar or alternative tools