Robbing Frenzy Risk Score Checker

Independently observed flight/entrance/store-contact evidence under caller robbing-monitoring criteria; not causal robbing diagnosis. Independently declared positive requirements, overlapping/unknown classes retained. Caller independently verifies strain, site, protocol and evidence; not colony-health, treatment, transport-safety or regulatory certification.

Description

Robbing assessment combines independently observed indicators with a declared rule set.

Robbing assessment combines independently observed indicators with a declared rule set.^[1]

Compatible observations do not create a universal frenzy probability or risk score. Use Robbing Frenzy Risk Score Checker to evaluate the supplied inputs under the model explained below.

When to use Robbing Frenzy Risk Score Checker

Use Robbing Frenzy Risk Score Checker to evaluate the supplied inputs under the model explained below. Define the candidate classes and their positive-evidence requirements, then distinguish evidence presence from whether it is known.

How to use Robbing Frenzy Risk Score Checker and understand its results

Define the candidate classes and their positive-evidence requirements, then distinguish evidence presence from whether it is known.
Enter Caller robbing observations class ids, Caller robbing observations requirements, Observed robbing observations evidence, Known robbing observations flags using the field table and validation rules below, then run the tool.
Read Compatible caller classes, Fully witnessed caller classes; interpret the units, signs, ordering and unknown-value placeholders described below.
Correct reported input errors and rerun. Apply successful results according to their specific meanings and check the assumptions before using them in a decision.

Input field	Meaning	Value type	Requirement
callerRobbingObservationsClassIds	Caller robbing observations class ids	array of string	Required; constraints below
callerRobbingObservationsRequirements	Caller robbing observations requirements	array of array	Required; constraints below
observedRobbingObservationsEvidence	Observed robbing observations evidence	array of number	Required; constraints below
knownRobbingObservationsFlags	Known robbing observations flags	array of number	Required; constraints below

Supply unique nonblank class IDs, one rectangular binary requirement row per class, and aligned binary observation and known-flag arrays. Each class must require at least one positive witness. Requirement 0 ignores an evidence column; requirement 1 needs a known positive observation for full witnessing. An unknown requirement remains compatible, while a known absent requirement excludes the class. Both returned class lists preserve caller order. No readiness rubric is installed and compatible does not mean fully witnessed or approved.

compatible = no required known absence; fully witnessed = every required witness known and positive

Use the field order, units and branch conditions described above.

Output field	Meaning	Value type
compatibleCallerClasses	Caller classes with no known absence of required positive evidence.	array of string
fullyWitnessedCallerClasses	Caller classes with all required positive evidence known and present.	array of string

json

{
  "input": {
    "callerRobbingObservationsClassIds": [
      "a",
      "b"
    ],
    "callerRobbingObservationsRequirements": [
      [
        1,
        0
      ],
      [
        0,
        1
      ]
    ],
    "observedRobbingObservationsEvidence": [
      1,
      0
    ],
    "knownRobbingObservationsFlags": [
      1,
      0
    ]
  },
  "output": {
    "compatibleCallerClasses": [
      "a",
      "b"
    ],
    "fullyWitnessedCallerClasses": [
      "a"
    ]
  }
}

Limitations and assumptions

Compatible observations do not create a universal frenzy probability or risk score. Apply the exact scope and assumptions explained above.

All listed fields require explicit values. Unexpected fields, incorrect types, nonfinite numbers and sparse arrays fail validation. Domain-specific bounds, alignments and supported tokens are explained above; extremely large inputs or outputs can also be rejected. Input errors differ from successful false results, empty match lists and unknown-evidence placeholders.

Alternative or Complementary methods

Use EFB Scale vs AFB Differential Lookup for a related task: Foulbrood differential references describe observations under a verified protocol.

Use AFB Ropey Matchstick Test Checker for a related task: A ropey-brood observation is evidence considered in foulbrood assessment.

References

Robbing Frenzy Risk Score Checker — tool.io

Similar or alternative tools

EFB Scale vs AFB Differential Lookup
Foulbrood differential references describe observations under a verified protocol.
AFB Ropey Matchstick Test Checker
A ropey-brood observation is evidence considered in foulbrood assessment.