Four-C Composite Grade Scorer

Caller explicitly independently normalized 4 C(not just cut-component) score aggregation with known-weight coverage; unavailable known score uses 0 with 0 coverage, no appraisal/laboratory grade. Caller independently establishes geometry, assay, calibration and protocol; not material identity, laboratory grade, treatment or care safety.

Description

The four Cs organize diamond descriptions around carat, color, clarity and cut.

The four Cs organize diamond descriptions around carat, color, clarity and cut.^{[1, 2]}

A custom weighted score requires explicit scales and missing-evidence coverage and is not a laboratory grade, price or standardized combined rating. Use this tool to calculate four-c composite grade scorer from the supplied measurements and assumptions.

When to use Four-C Composite Grade Scorer

Use this tool to calculate four-c composite grade scorer from the supplied measurements and assumptions. Establish the specimen, measurement protocol, units, geometry and any caller calibration or review limits.

How to use Four-C Composite Grade Scorer and understand its results

Establish the specimen, measurement protocol, units, geometry and any caller calibration or review limits.
Enter callerIndependentlyCalibratedFourCScores, callerFourCWeights, knownFourCFlags, using the field meanings and rules below, then run the tool.
Read knownFourCWeightedScore, knownWeightFraction, completeFourCEvidence. Interpret the fields using their units, signs and evidence conventions below.
If input validation fails, correct the reported field and run again. Before applying the result, check reference scope, model assumptions and any missing evidence or placeholder values.

Input field	Meaning	Value type	Requirement
callerIndependentlyCalibratedFourCScores	Caller independently calibrated four c scores; caller assertion or measurement requiring independent evidence	list of number	Required
callerFourCWeights	Caller four c weights	list of number	Required
knownFourCFlags	Known four c flags; binary 1=known, 0=unknown, in the order described below	list of number	Required

Enter exactly four independently calibrated scores in [0,1], four nonnegative weights and four binary known flags in cut, color, clarity, carat order. Require positive total weight. Divide the known weighted score sum by known weight when it is positive, otherwise return placeholder score 0; report knownWeight/totalWeight. completeFourCEvidence requires all four known flags to be 1, even for a zero-weight criterion. The score normalization is caller-defined; preserve the fixed cut, color, clarity, carat ordering.

knownScore=knownWeight>0 ? Σ(score×weight×known)/knownWeight : 0; coverage=knownWeight/totalWeight; complete=all known flags 1

Use the exact units, boundary rules, ordering and missing-evidence conventions above.

Output field	Meaning	Value type
knownFourCWeightedScore	Weighted mean of known scores; placeholder 0 when known weight is zero	number
knownWeightFraction	Known criterion weight divided by total weight	number
completeFourCEvidence	True only when all four criteria are marked known, including zero-weight criteria	boolean

json

{
  "input": {
    "callerIndependentlyCalibratedFourCScores": [
      0.8,
      0.6,
      0.4,
      1
    ],
    "callerFourCWeights": [
      1,
      1,
      1,
      1
    ],
    "knownFourCFlags": [
      1,
      1,
      1,
      0
    ]
  },
  "output": {
    "knownFourCWeightedScore": 0.6,
    "knownWeightFraction": 0.75,
    "completeFourCEvidence": false
  }
}

Limitations and assumptions

A custom weighted score requires explicit scales and missing-evidence coverage and is not a laboratory grade, price or standardized combined rating. Interpretation depends on the units, sampling scope and exact model described above.

All listed fields require explicit values. Unexpected fields, incorrect types, nonfinite numbers and sparse evidence arrays fail validation; the specific bounds and alignment requirements are stated above. Extremely large inputs or outputs can also be rejected. An input error is distinct from a successful result reporting false, no matches or missing evidence.

Alternative or Complementary methods

Use Mohs Interval Wear Suitability Checker for this related task: Wear suitability includes more than scratch hardness, such as toughness, stability and the planned setting.

Use Facet Count by Cut Type Lookup when its separate inputs and assumptions fit the question: Facet-count conventions depend on the cut design and on which surfaces are counted as facets.

References

Four-C Composite Grade Scorer — tool.io
Diamond Quality Factors — Gemological Institute of America

Similar or alternative tools

Mohs Interval Wear Suitability Checker
Wear suitability includes more than scratch hardness, such as toughness, stability and the planned setting.
Facet Count by Cut Type Lookup
Facet-count conventions depend on the cut design and on which surfaces are counted as facets.