Domain Guide

Guide Maps

graph LR
  family["Reproducible Research"]
  program["Deep Dive DVC"]
  guide["Capstone docs"]
  section["Docs"]
  page["Domain Guide"]
  proof["Proof route"]

  family --> program --> guide --> section --> page
  page -.checks against.-> proof

flowchart LR
  orient["Read the guide boundary"] --> inspect["Inspect the named files, targets, or artifacts"]
  inspect --> run["Run the confirm, demo, selftest, or proof command"]
  run --> compare["Compare output with the stated contract"]
  compare --> review["Return to the course claim with evidence"]

Use this guide when the capstone feels structurally clear but the modeled problem still feels abstract. The goal is to make the incident-escalation story concrete before you reason about DVC state and review routes.

What the raw dataset represents

The repository models service incidents that may or may not escalate into a broader operational response. Each row describes one incident with a small feature set that a team could plausibly review before deciding whether closer intervention is likely.

Column meanings

Column	Meaning	Why it matters
incident_id	stable incident identifier	keeps split logic and review examples tied to a real record
team	owning service or platform team	lets prediction review stay anchored in operational ownership
backlog_days	age of the incident in days	captures unresolved operational pressure
reopened_count	number of reopen events	captures churn and instability
integration_touchpoints	number of connected systems involved	captures coordination breadth
customer_tier	customer criticality bucket	captures business impact pressure
weekend_handoff	whether the incident crossed a weekend handoff	captures time-and-coordination friction
severity_score	numeric severity proxy	captures direct operational urgency
escalated	whether the incident escalated	is the target outcome the model predicts

What the publish bundle is trying to help a reviewer answer

• what population the model saw and evaluated
• what threshold was used for the promoted decision policy
• which eval rows were predicted correctly or incorrectly
• whether the promoted metrics describe a problem a human can still reason about later

Best companion guides

• read Capstone Architecture when the domain is clear but the repository ownership layers are not
• read Experiment Guide when the next question is how declared controls change the review meaning
• read Publish Contract when the next question is which domain evidence survives into publish/v1/