Voges-Proskauer Acetoin Red Layer Positive Classifier
Record independently observed Voges-Proskauer Acetoin Red Layer Positive Classifier evidence with explicit knownness and valid controls. Does not inspect images, infer species, diagnose infection or recommend treatment.
Description
Record a supplied Voges–Proskauer color observation without measuring acetoin or establishing a diagnosis.
A Voges–Proskauer color observation is one assay feature rather than an organism identification. Keeping validity flags prevents an unobserved or invalid reaction from becoming a negative label.
When to use this tool
Record a supplied Voges–Proskauer color observation without measuring acetoin or establishing a diagnosis.
- Prepare the supplied redAcetoinLayer, observationKnown, controlValid fields for this operation.
- Compare the complete example with the representation used by your own input before carrying the result into another step.
How to use the tool and how it works
- Enter redAcetoinLayer, observationKnown, controlValid. Use the exact text syntax, units and index conventions explained below.
- Run the tool. If input validation fails, correct the supplied fields before interpreting any result.
- Read result.assayObservation, result.diagnosticConclusion. Interpret false, null and empty lists using the distinctions below; they can be valid outputs.
Supply redAcetoinLayer as true for the observed feature or false for its observed absence, together with explicit observationKnown and controlValid booleans. Return assayObservation indeterminate if observationKnown is false or controlValid is false; otherwise return positive when redAcetoinLayer is true and negative when false. Return diagnosticConclusion as not-established in every case. No image processing or measurement is performed.1
| Input field | Meaning and representation | Accepted input |
|---|---|---|
| redAcetoinLayer | Explicit choice for red acetoin layer; supply a boolean rather than a text label. | true or false |
| observationKnown | True only when the feature observation is actually known; false preserves an indeterminate/unknown outcome. | true or false |
| controlValid | Whether the relevant assay control or observation-validity condition is established. | true or false |
| Output field | Interpretation |
|---|---|
| result | Object containing the named outputs below. |
| result.assayObservation | Positive or negative only when both observation and control validity are established; indeterminate otherwise. |
| result.diagnosticConclusion | Always not-established: the recorded feature does not establish a diagnosis. |
{
"input": {
"redAcetoinLayer": true,
"observationKnown": true,
"controlValid": true
},
"output": {
"result": {
"assayObservation": "positive",
"diagnosticConclusion": "not-established"
}
}
}Limitations and assumptions
- The tool does not add reagents, time a reaction, inspect a layer or measure acetoin. redAcetoinLayer is supplied by the caller; no diagnostic conclusion follows.
- Every declared top-level field is required and unexpected fields are rejected. Numeric inputs must be finite; ordinary text fields are bounded to 8,192 UTF-16 code units, with tighter operation-specific limits where stated.
- Ordinary string lists have at most 128 entries of at most 128 code units each; numeric lists and matrices have separate bounded size checks. Nonfinite results and excessively large serialized outputs are rejected.
- Indexes are zero-based and spans have an exclusive end unless explicitly stated otherwise. A valid false, null or empty-list result is distinct from malformed input.
Alternative or Complementary methods
Retain specimen context, controls and independently observed features alongside a test label. Use a complete validated identification or analytical workflow when conclusions require several assays; a single stored morphology definition, feature flag or threshold comparison does not identify an organism.
References
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