Dontopedia

Default Estimate Branch

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-07.)

Default Estimate Branch is Use a default estimate if no similar tasks are found.

5 facts·4 predicates·1 sources·1 in dispute

Mostly:uses variable(2), rdf:type(1), description(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (4)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

containsContains(1)

hasBranchHas Branch(1)

hasFalseBranchHas False Branch(1)

hasPartHas Part(1)

Other facts (5)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

5 facts
PredicateValueRef
Uses VariableTask Complexity[1]
Uses VariableAverage Ratio[1]
Rdf:typeConditional Branch[1]
DescriptionUse a default estimate if no similar tasks are found[1]
Assigns toAdjusted Estimate[1]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

typebeam/a7533162-46e0-421d-9dc2-7eb6cd90188e
ex:ConditionalBranch
descriptionbeam/a7533162-46e0-421d-9dc2-7eb6cd90188e
Use a default estimate if no similar tasks are found
usesVariablebeam/a7533162-46e0-421d-9dc2-7eb6cd90188e
ex:task-complexity
usesVariablebeam/a7533162-46e0-421d-9dc2-7eb6cd90188e
ex:average-ratio
assignsTobeam/a7533162-46e0-421d-9dc2-7eb6cd90188e
ex:adjusted-estimate

References (1)

1 references
  1. ctx:claims/beam/a7533162-46e0-421d-9dc2-7eb6cd90188e
    • full textbeam-chunk
      text/plain990 Bdoc:beam/a7533162-46e0-421d-9dc2-7eb6cd90188e
      Show excerpt
      # Calculate the average estimated hours for similar tasks average_estimated_hours = similar_tasks['estimated_hours'].mean() # Adjust the estimate based on the average ratio adjusted_estimate = averag

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