Mohs Interval Wear Suitability Checker

Caller independently documented hardness/toughness/cleavage/exposure evidence against caller wearing-context review criteria, no Mohs-only safe suitability verdict. Independently declared positive evidence requirements; overlaps and unknowns retained. Caller independently establishes geometry, assay, calibration and protocol; not material identity, laboratory grade, treatment or care safety.

Description

Wear suitability includes more than scratch hardness, such as toughness, stability and the planned setting.

Wear suitability includes more than scratch hardness, such as toughness, stability and the planned setting.^[1]

A caller-defined evidence table compares documented criteria without supplying a universal gemstone-wear recommendation. Use this tool to calculate mohs interval wear suitability checker from the supplied measurements and assumptions.

When to use Mohs Interval Wear Suitability Checker

Use this tool to calculate mohs interval wear suitability checker from the supplied measurements and assumptions. Establish the specimen, measurement protocol, units, geometry and any caller calibration or review limits.

How to use Mohs Interval Wear Suitability Checker and understand its results

Establish the specimen, measurement protocol, units, geometry and any caller calibration or review limits.
Enter callerWearReviewClassIds, callerWearReviewRequirements, observedWearReviewEvidence, knownWearReviewFlags, using the field meanings and rules below, then run the tool.
Read compatibleCallerClasses, fullyWitnessedCallerClasses. 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
callerWearReviewClassIds	Caller wear review class ids	list of string	Required
callerWearReviewRequirements	Caller wear review requirements	list of list of number	Required
observedWearReviewEvidence	Observed wear review evidence	list of number	Required
knownWearReviewFlags	Known wear review flags; binary 1=known, 0=unknown, in the order described below	list of number	Required

Supply nonempty unique class IDs and a rectangular binary requirement matrix with one row per class and one column per observed feature. Every class must require at least one positive feature. Supply aligned binary observation and known-flag lists. A requirement 0 ignores its column; a requirement 1 permits a class only if the feature is unknown or observed present. Fully witnessed classes require every required feature to be known present. Return all compatible and fully witnessed caller classes in caller order; unknown evidence can leave several candidates, and known absent required evidence excludes a class. The rubric is supplied rather than installed.

compatible={class:each required column is unknown or present}; witnessed={class:each required column is known present}

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

Output field	Meaning	Value type
compatibleCallerClasses	Every supplied class whose required features are unknown or known present	list of string
fullyWitnessedCallerClasses	Every supplied class with all required features known present	list of string

json

{
  "input": {
    "callerWearReviewClassIds": [
      "a",
      "b"
    ],
    "callerWearReviewRequirements": [
      [
        1,
        0
      ],
      [
        0,
        1
      ]
    ],
    "observedWearReviewEvidence": [
      1,
      0
    ],
    "knownWearReviewFlags": [
      1,
      0
    ]
  },
  "output": {
    "compatibleCallerClasses": [
      "a",
      "b"
    ],
    "fullyWitnessedCallerClasses": [
      "a"
    ]
  }
}

Limitations and assumptions

A caller-defined evidence table compares documented criteria without supplying a universal gemstone-wear recommendation. 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 Scratch Hardness Gap Calculator for this related task: Mohs hardness is an ordinal scratch-resistance scale rather than a linear measure of abrasive wear.

Use Four-C Composite Grade Scorer when its separate inputs and assumptions fit the question: The four Cs organize diamond descriptions around carat, color, clarity and cut.

References

Mohs Interval Wear Suitability Checker — tool.io

Similar or alternative tools

Scratch Hardness Gap Calculator
Mohs hardness is an ordinal scratch-resistance scale rather than a linear measure of abrasive wear.
Four-C Composite Grade Scorer
The four Cs organize diamond descriptions around carat, color, clarity and cut.