Heterobasidion Stump Infection Probability Calculator
Summarize independently identified Heterobasidion stump infection observations with unknown bounds, not predicted pathogen infection probability or treatment instructions. Caller independently verifies units, applicability and matching conditions; no operational recipe, safety certification, causal efficacy or legal/resource classification is inferred.
Description
Observed infection incidence counts infected assessed stumps relative to all assessed stumps.
Observed infection incidence counts infected assessed stumps relative to all assessed stumps.1
Treating unassessed stumps as a bounded unknown contribution gives possible total-incidence limits without predicting future spread. Use this tool to calculate heterobasidion stump infection probability from the supplied measurements and assumptions.
When to use Heterobasidion Stump Infection Probability Calculator
Use this tool to calculate heterobasidion stump infection probability from the supplied measurements and assumptions. Establish the species/site, survey protocol, units, sampled area or exposure, and the independently chosen reference or model.
How to use Heterobasidion Stump Infection Probability Calculator and understand its results
- Establish the species/site, survey protocol, units, sampled area or exposure, and the independently chosen reference or model.
- Enter observedAssessedStumpCounts, observedInfectedStumpCounts, callerUnassessedStumpCounts, using the field meanings and rules below, then run the tool.
- Read observedAssessedStumpInfectionFraction, wholeStumpInfectionLowerBound, wholeStumpInfectionUpperBound. 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 |
|---|---|---|---|
| observedAssessedStumpCounts | Observed assessed stump counts | list of number | Required |
| observedInfectedStumpCounts | Observed infected stump counts | list of number | Required |
| callerUnassessedStumpCounts | Caller unassessed stump counts | list of number | Required |
Enter nonempty aligned nonnegative integer infected, assessed and unassessed stump counts bounded to 1,000,000, requiring infected≤assessed in every group and a positive assessed total. Return infectedTotal/assessedTotal plus full-sample lower=infected/(assessed+unknown) and upper=(infected+unknown)/(assessed+unknown). These are fractions, not percent-scaled results or future infection probabilities.
observed=Σinfected/Σassessed; lower=Σinfected/Σ(assessed+unknown); upper=Σ(infected+unknown)/Σ(assessed+unknown) Use the exact units, boundary rules, ordering and missing-evidence conventions above.
| Output field | Meaning | Value type |
|---|---|---|
| observedAssessedStumpInfectionFraction | Observed Assessed Stump Infection Fraction; follow the units, sign, ordering and evidence convention stated above | number |
| wholeStumpInfectionLowerBound | Whole Stump Infection Lower Bound; follow the units, sign, ordering and evidence convention stated above | number |
| wholeStumpInfectionUpperBound | Whole Stump Infection Upper Bound; follow the units, sign, ordering and evidence convention stated above | number |
{
"input": {
"observedAssessedStumpCounts": [
10,
20
],
"observedInfectedStumpCounts": [
1,
4
],
"callerUnassessedStumpCounts": [
2,
3
]
},
"output": {
"observedAssessedStumpInfectionFraction": 0.16666666666666666,
"wholeStumpInfectionLowerBound": 0.14285714285714285,
"wholeStumpInfectionUpperBound": 0.2857142857142857
}
}Limitations and assumptions
Treating unassessed stumps as a bounded unknown contribution gives possible total-incidence limits without predicting future spread. 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 Rust Gall Incidence Stem Sweep Frequency for this related task: Rust-gall incidence is the proportion of assessed observations with a recorded gall.
Use Dutch Elm Disease Sanitation Pressure Checker when its separate inputs and assumptions fit the question: A sanitation record can compare infected material with material independently recorded as removed.
References
Similar or alternative tools
- Rust Gall Incidence Stem Sweep Frequency
Rust-gall incidence is the proportion of assessed observations with a recorded gall.
- Dutch Elm Disease Sanitation Pressure Checker
A sanitation record can compare infected material with material independently recorded as removed.