Scenario Consistency Driver Coherence Checker

Check whether drivers assigned to the same coherence group use consistent signed effects on shared outcomes.

Description

A scenario coherence check can expose opposing signs assigned to the same outcome within a shared driver group.

A scenario coherence check can expose opposing signs assigned to the same outcome within a shared driver group. Neutral signs do not contradict active signs.^[1]

The returned values include Active effects, Scenario coherent, Contradictory driver-outcome pairs, Inconsistent driver IDs. The How section below explains the calculation, input rules and interpretation.

When to use Scenario Consistency Driver Coherence Checker

Use Scenario Consistency Driver Coherence Checker when you need to evaluate the supplied records under the calculation and evidence rules below. No contradiction is checked across different groups or inferred from narrative text.

Define the question, evidence and scenario assumptions first. Supply the chosen score scales, time horizons or reference selection explicitly. Interpret generated text as a discussion template and screen labels as the stated rules.

How to use Scenario Consistency Driver Coherence Checker and understand its results

Define the question, evidence and scenario assumptions first. Supply the chosen score scales, time horizons or reference selection explicitly. Interpret generated text as a discussion template and screen labels as the stated rules.
Enter coherenceGroupIds, driverIds, effectSigns, outcomeIds using the field table and calculation rules, then run the tool.
Read activeEffectCount, coherent, contradictionPairs, inconsistentDriverIds. 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
coherenceGroupIds	One coherence-group label per driver.	list of string	Required
driverIds	Driver IDs	list of string	Required
effectSigns	A driver-by-outcome matrix containing -1, 0, or 1.	list of list of number	Required
outcomeIds	Outcome IDs	list of string	Required

Require unique trimmed drivers, matching nonblank groups, nonempty nonblank outcomes and driver-by-outcome rows of −1/0/1. Compare driver pairs in input order and each outcome in order; collect conflicting pairs and first-encounter involved drivers. Return active nonzero count and flag for no pairs. Outcome labels may repeat.

contradiction=sameGroup AND nonzero opposing signs

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output field	Meaning	Value type
activeEffectCount	Active effects	integer; minimum: 0
coherent	Scenario coherent	boolean
contradictionPairs	Contradictory driver-outcome pairs	list of string
inconsistentDriverIds	Inconsistent driver IDs	list of string

json

{
  "input": {
    "coherenceGroupIds": [
      "demand",
      "supply",
      "demand"
    ],
    "driverIds": [
      "Adoption",
      "Capacity",
      "Cost"
    ],
    "effectSigns": [
      [
        1,
        1
      ],
      [
        1,
        1
      ],
      [
        -1,
        -1
      ]
    ],
    "outcomeIds": [
      "Volume",
      "Price"
    ]
  },
  "output": {
    "activeEffectCount": 6,
    "coherent": false,
    "contradictionPairs": [
      "Adoption vs Cost on Volume",
      "Adoption vs Cost on Price"
    ],
    "inconsistentDriverIds": [
      "Adoption",
      "Cost"
    ]
  }
}

Limitations and assumptions

No contradiction is checked across different groups or inferred from narrative text.

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. A successfully returned false flag is an evaluated outcome; its meaning is explained above.

Alternative or Complementary methods

Use Cross Impact Analysis Event Pair Matrix: Cross-impact matrices distinguish directed relationships between events. Positive and negative scores need separate interpretation. For a complementary task, use Urbanization Driver Implication Chain Builder: A driver graph records directed implications. Reachability identifies which listed drivers can be reached from a chosen root.

References

Scenario Consistency Driver Coherence Checker — tool.io

Similar or alternative tools

Cross Impact Analysis Event Pair Matrix
Cross-impact matrices distinguish directed relationships between events. Positive and negative scores need separate interpretation.
Urbanization Driver Implication Chain Builder
A driver graph records directed implications. Reachability identifies which listed drivers can be reached from a chosen root.