Creepypasta Viral Generation Count Model
Conditional branching expectation for creepypasta reports with constant independently assumed reproduction, no saturation or network overlap. Fractional expectations allowed; reports are not unique people or validated viral predictions.
Description
A generation model projects repeated transmission from a starting number of reports.
A generation model projects repeated transmission from a starting number of reports.1
Its multiplication factor is an assumption, so the result is an expected sequence rather than observed viral spread. Use this tool to calculate creepypasta Viral Generation Count Model from the supplied measurements and assumptions.
When to use Creepypasta Viral Generation Count Model
Use this tool to calculate creepypasta Viral Generation Count Model from the supplied measurements and assumptions. Identify the community, narrative version, source edition and interpretation context; prepare any annotations independently.
How to use Creepypasta Viral Generation Count Model and understand its results
- Identify the community, narrative version, source edition and interpretation context; prepare any annotations independently.
- Enter initialSeedReports, independentlyAssumedNewReportsPerReport, generations, using the field meanings and rules below, then run the tool.
- Read result.expectedNewReportsByGeneration, result.expectedCumulativeReports. 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 |
|---|---|---|---|
| initialSeedReports | Initial seed reports | number | Required |
| independentlyAssumedNewReportsPerReport | Independently assumed new reports per report; caller assertion or measurement requiring independent evidence | number | Required |
| generations | Generations | number | Required |
Enter integer initial reports from zero to 1,000,000, integer generations from zero to 64 and a nonnegative reproduction factor. Start with the seed as generation zero, multiply successively through the selected generation, and sum all entries. Fractional expected reports are allowed; nonfinite projections fail. No deduplication, population cap or stochastic contagion is modeled.
reports_g=seed×factor^g for g=0..generations; total=Σreports_g Use the exact units, boundary rules, ordering and missing-evidence conventions above.
| Output field | Meaning | Value type |
|---|---|---|
| result | Structured calculation or selected reference, with fields listed below | object |
| result.expectedNewReportsByGeneration | Expected New Reports By Generation; follow the units, sign, ordering and evidence convention stated above | list of number |
| result.expectedCumulativeReports | Expected Cumulative Reports; follow the units, sign, ordering and evidence convention stated above | number |
{
"input": {
"initialSeedReports": 2,
"independentlyAssumedNewReportsPerReport": 3,
"generations": 2
},
"output": {
"result": {
"expectedNewReportsByGeneration": [
2,
6,
18
],
"expectedCumulativeReports": 26
}
}
}Limitations and assumptions
Its multiplication factor is an assumption, so the result is an expected sequence rather than observed viral 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 Chain Letter Blessing Threat Clause Classifier for this related task: Chain letters may combine promised benefits, threats and pressure to forward a message.
Use Foaf Friend of a Friend Chain Depth Lookup when its separate inputs and assumptions fit the question: A friend-of-a-friend chain records successive links between a report and its attributed source.
References
-
Creepypasta Viral Generation Count Model — tool.io
Similar or alternative tools
- Chain Letter Blessing Threat Clause Classifier
Chain letters may combine promised benefits, threats and pressure to forward a message.
- Foaf Friend of a Friend Chain Depth Lookup
A friend-of-a-friend chain records successive links between a report and its attributed source.