Nail-Head Proportion Flag Calculator

Actual independently measured central darkness under matched illumination against caller nail-head screen; depth alone not diagnosis. Missing evidence retained as explicit indices, not confirmed zero margin. Caller independently establishes geometry, assay, calibration and protocol; not material identity, laboratory grade, treatment or care safety.

Description

A nail-head appearance is an observed dark central region under a specified viewing protocol.

A nail-head appearance is an observed dark central region under a specified viewing protocol.1

Comparing measurements with supplied limits does not establish an optical cause or the overall quality of a cut. Use this tool to calculate nail-head proportion flag from the supplied measurements and assumptions.

When to use Nail-Head Proportion Flag Calculator

Use this tool to calculate nail-head proportion flag from the supplied measurements and assumptions. Establish the specimen, measurement protocol, units, geometry and any caller calibration or review limits.

How to use Nail-Head Proportion Flag Calculator and understand its results

  1. Establish the specimen, measurement protocol, units, geometry and any caller calibration or review limits.
  2. Enter observedObservedNailHeadDarkness, callerObservedNailHeadDarknessLower, callerObservedNailHeadDarknessUpper, knownObservedNailHeadDarknessFlags, using the field meanings and rules below, then run the tool.
  3. Read signedKnownMargins, knownReviewIndices, unknownIndices. Interpret the fields using their units, signs and evidence conventions below.
  4. 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 fieldMeaningValue typeRequirement
observedObservedNailHeadDarknessObserved observed nail head darknesslist of numberRequired
callerObservedNailHeadDarknessLowerCaller observed nail head darkness lowerlist of numberRequired
callerObservedNailHeadDarknessUpperCaller observed nail head darkness upperlist of numberRequired
knownObservedNailHeadDarknessFlagsKnown observed nail head darkness flags; binary 1=known, 0=unknown, in the order described belowlist of numberRequired

Enter nonempty aligned measurements, lower bounds, upper bounds and binary known flags. Each upper bound must be at least its lower bound, including equal bounds. For known observations calculate the smaller of measured−lower and upper−measured; an outside observation has a negative margin and its zero-based index enters knownReviewIndices. Equality is inside the window. Unknown observations receive placeholder margin 0 and their indices enter unknownIndices; that 0 does not mean an observed pass. Bounds are caller inputs, with no installed optical threshold or ray-tracing model.

margin_i=known_i ? min(observed_i−lower_i,upper_i−observed_i) : 0; review={i:known_i and (observed_i<lower_i or observed_i>upper_i)}

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

Output fieldMeaningValue type
signedKnownMarginsPer-item smaller distance to either bound; negative outside, zero placeholder for unknown itemslist of number
knownReviewIndicesZero-based indices of known observations strictly outside the supplied inclusive windowlist of values
unknownIndicesZero-based indices of observations marked unknownlist of number
json
{
  "input": {
    "observedObservedNailHeadDarkness": [
      2,
      5
    ],
    "callerObservedNailHeadDarknessLower": [
      1,
      1
    ],
    "callerObservedNailHeadDarknessUpper": [
      3,
      4
    ],
    "knownObservedNailHeadDarknessFlags": [
      1,
      0
    ]
  },
  "output": {
    "signedKnownMargins": [
      1,
      0
    ],
    "knownReviewIndices": [],
    "unknownIndices": [
      1
    ]
  }
}

Limitations and assumptions

Comparing measurements with supplied limits does not establish an optical cause or the overall quality of a cut. 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 Window Effect Depth Check for Cabs for this related task: A central window is an optical appearance observed under a defined illumination and viewing geometry.

Use Fish-Eye Detection Depth Check when its separate inputs and assumptions fit the question: A fish-eye appearance is a particular observed optical feature under a defined viewing setup.

References

  1. Nail-Head Proportion Flag Calculator — tool.io

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