Evidence Relevance Reliability Two-Axis Lookup
Classify supplied one-to-five reliability and relevance ratings into high, mixed, and low evidence quadrants and retain indices of low evidence.
Description
Evidence relevance and reliability describe different dimensions.
Evidence relevance and reliability describe different dimensions. This implementation combines their entered ratings by addition.1
The returned values include High evidence count, Low evidence count, Low evidence indices, Mixed evidence count. The How section below explains the calculation, input rules and interpretation.
When to use Evidence Relevance Reliability Two-Axis Lookup
Use Evidence Relevance Reliability Two-Axis Lookup when you need to evaluate the supplied records under the calculation and evidence rules below. No separate quadrant threshold, evidence authenticity or audit sufficiency conclusion is established.
Prepare source-backed observations and the applicable engagement policy before entering facts. Use consistent monetary units and periods. Supply all boolean evidence flags explicitly, and treat a successful screen as a reason to continue professional review.
How to use Evidence Relevance Reliability Two-Axis Lookup and understand its results
- Prepare source-backed observations and the applicable engagement policy before entering facts. Use consistent monetary units and periods. Supply all boolean evidence flags explicitly, and treat a successful screen as a reason to continue professional review.
- Enter assessments using the field table and calculation rules, then run the tool.
- Read highEvidenceCount, lowEvidenceCount, lowEvidenceIndices, mixedEvidenceCount. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
| Input field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| assessments | Rows ordered as reliability and relevance ratings from 1 through 5. | list of list of number | Required |
Supply possibly empty rows of two safe-integer ratings 1–5. Return category counts and zero-based low indexes. A5/3 pair is high just like4/4.
combined=reliability+relevance; high≥8,mixed≥5,otherwise low Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| highEvidenceCount | High evidence count | integer; minimum: 0 |
| lowEvidenceCount | Low evidence count | integer; minimum: 0 |
| lowEvidenceIndices | Low evidence indices | list of number |
| mixedEvidenceCount | Mixed evidence count | integer; minimum: 0 |
{
"input": {
"assessments": [
[
5,
5
],
[
4,
3
],
[
2,
2
]
]
},
"output": {
"highEvidenceCount": 1,
"lowEvidenceCount": 1,
"lowEvidenceIndices": [
2
],
"mixedEvidenceCount": 1
}
}Limitations and assumptions
No separate quadrant threshold, evidence authenticity or audit sufficiency conclusion is established.
Numeric inputs, where present, must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Core numeric and string lists are limited to 100,000 entries; text entries are subject to the general large-text limit. Follow any smaller calculation limits above. Matrices are limited to 128 rows and 128 entries per row. Missing fields without a declared default, extra fields, wrong value types and violations of the calculation rules are input errors.
Alternative or Complementary methods
Use Evidence Hierarchy External Confirmation Ranking Table: An evidence hierarchy ranks source types according to a supplied policy. Relative rank depends on that entered ordering. For a complementary task, use Data Reliability Completeness Accuracy Source Testing Steps: Data reliability requires evidence about source, completeness, accuracy and reconciliation. Entered facts produce this transparent four-criterion screen.
References
Similar or alternative tools
- Evidence Hierarchy External Confirmation Ranking Table
An evidence hierarchy ranks source types according to a supplied policy. Relative rank depends on that entered ordering.
- Data Reliability Completeness Accuracy Source Testing Steps
Data reliability requires evidence about source, completeness, accuracy and reconciliation. Entered facts produce this transparent four-criterion screen.