Mintmark Record Match
Compare caller-supplied expected and observed records for mintmark record match.
Description
Mintmark records associate documented mark labels with an issue context.
Mintmark records associate documented mark labels with an issue context. Set matching identifies observed labels outside a supplied expected list.1
Compare caller-supplied expected and observed records for mintmark record match.
When to use Mintmark Record Match
Use this tool to compare caller-supplied expected and observed records for mintmark record match.
Prepare documented records or observations for the specific coin or issue context. Enter the required labels, reference table or evidence flags and retain the supporting catalog and examination notes for interpretation.
How to use Mintmark Record Match and understand its results
- Prepare documented records or observations for the specific coin or issue context. Enter the required labels, reference table or evidence flags and retain the supporting catalog and examination notes for interpretation.
- Enter documentedMintmarks, observedMintmarks using the field table and calculation rules, then run the tool.
- Read coveragePercent, matched, missing, unexpected. 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 |
|---|---|---|---|
| documentedMintmarks | Documented mintmarks | list of string | Required |
| observedMintmarks | Observed mintmarks | list of string | Required |
Enter expected and observed lists using the field table. Trim, reject blank entries and normalize keys with en-US lowercase. Deduplicate both lists, requiring at least one distinct expected item; observations may be empty. Return matched/missing labels in expected order, unexpected labels in observed order and coverage. Last duplicate spelling is retained at its first key position.
coverage%=100 matchedDistinctExpected/distinctExpected Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| coveragePercent | Coverage (%) | number; minimum: 0; maximum: 100 |
| matched | Matched items | list of string |
| missing | Missing items | list of string |
| unexpected | Unexpected items | list of string |
{
"input": {
"documentedMintmarks": [
"P",
"D",
"S"
],
"observedMintmarks": [
"D",
"S",
"O"
]
},
"output": {
"coveragePercent": 66.66666666666666,
"matched": [
"D",
"S"
],
"missing": [
"P"
],
"unexpected": [
"O"
]
}
}Limitations and assumptions
No embedded mintmark catalog, mint attribution or image recognition is included. Case and outer whitespace are ignored, while other spelling differences remain distinct.
Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Lists are limited to 100,000 entries; the rules above may require smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.
Alternative or Complementary methods
Use Cob Assayer Record Match: Compare caller-supplied expected and observed records for cob assayer record match. For a complementary task, use Alexander Drachm Monogram Record Lookup: Look up a monogram only within a caller-supplied, parallel mint-and-reference dataset; the mark alone is not treated as a universal mint attribution.
References
-
Mintmark Record Match — tool.io
Similar or alternative tools
- Cob Assayer Record Match
Compare caller-supplied expected and observed records for cob assayer record match.
- Alexander Drachm Monogram Record Lookup
Look up a monogram only within a caller-supplied, parallel mint-and-reference dataset; the mark alone is not treated as a universal mint attribution.