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          "readinessContribution": 0,
          "riskContribution": 0,
          "rank": 3,
          "pareto": "Non-dominated"
        }
      ]
    },
    {
      "title": "Contribution to the weighted score",
      "columns": [
        {
          "key": "name",
          "label": "Alternative",
          "unit": ""
        },
        {
          "key": "costContribution",
          "label": "Capital cost",
          "unit": "points"
        },
        {
          "key": "impactContribution",
          "label": "Strategic impact",
          "unit": "points"
        },
        {
          "key": "readinessContribution",
          "label": "Readiness",
          "unit": "points"
        },
        {
          "key": "riskContribution",
          "label": "Execution risk",
          "unit": "points"
        },
        {
          "key": "score",
          "label": "Total score",
          "unit": "points"
        }
      ],
      "rows": [
        {
          "name": "A",
          "score": 99.9999999999,
          "costContribution": 99.9999999999,
          "impactContribution": 0,
          "readinessContribution": 0,
          "riskContribution": 0,
          "rank": 1
        },
        {
          "name": "B",
          "score": 87.5000000000125,
          "costContribution": 87.4999999999125,
          "impactContribution": 9.99999999999e-11,
          "readinessContribution": 0,
          "riskContribution": 0,
          "rank": 2
        },
        {
          "name": "C",
          "score": 0,
          "costContribution": 0,
          "impactContribution": 0,
          "readinessContribution": 0,
          "riskContribution": 0,
          "rank": 3
        }
      ]
    },
    {
      "title": "Preference-weight sensitivity",
      "columns": [
        {
          "key": "criterion",
          "label": "Changed criterion",
          "unit": ""
        },
        {
          "key": "shift",
          "label": "Weight shift",
          "unit": "percentage points"
        },
        {
          "key": "testedWeight",
          "label": "Tested weight",
          "unit": "%"
        },
        {
          "key": "tiedLeaders",
          "label": "Leading alternatives",
          "unit": ""
        },
        {
          "key": "leaderScore",
          "label": "Score",
          "unit": "/100"
        },
        {
          "key": "originalLeaderRank",
          "label": "Base leader rank",
          "unit": ""
        },
        {
          "key": "ranking",
          "label": "Complete ordering",
          "unit": ""
        }
      ],
      "rows": [
        {
          "criterion": "Capital cost",
          "shift": -20,
          "testedWeight": 79.9999999999,
          "leader": "B",
          "leaderScore": 90.0000000000125,
          "originalLeaderRank": 2,
          "ranking": "B → A → C",
          "tiedLeaders": [
            "B"
          ]
        },
        {
          "criterion": "Capital cost",
          "shift": 20,
          "testedWeight": 100,
          "leader": "A",
          "leaderScore": 100,
          "originalLeaderRank": 1,
          "ranking": "A → B → C",
          "tiedLeaders": [
            "A"
          ]
        },
        {
          "criterion": "Strategic impact",
          "shift": -20,
          "testedWeight": 0,
          "leader": "A",
          "leaderScore": 100,
          "originalLeaderRank": 1,
          "ranking": "A → B → C",
          "tiedLeaders": [
            "A"
          ]
        },
        {
          "criterion": "Strategic impact",
          "shift": 20,
          "testedWeight": 20.0000000001,
          "leader": "B",
          "leaderScore": 90.0000000000125,
          "originalLeaderRank": 2,
          "ranking": "B → A → C",
          "tiedLeaders": [
            "B"
          ]
        },
        {
          "criterion": "Readiness",
          "shift": -20,
          "testedWeight": 0,
          "leader": "A",
          "leaderScore": 99.9999999999,
          "originalLeaderRank": 1,
          "ranking": "A → B → C",
          "tiedLeaders": [
            "A"
          ]
        },
        {
          "criterion": "Readiness",
          "shift": 20,
          "testedWeight": 20,
          "leader": "A",
          "leaderScore": 79.99999999992,
          "originalLeaderRank": 1,
          "ranking": "A → B → C",
          "tiedLeaders": [
            "A"
          ]
        },
        {
          "criterion": "Execution risk",
          "shift": -20,
          "testedWeight": 0,
          "leader": "A",
          "leaderScore": 99.9999999999,
          "originalLeaderRank": 1,
          "ranking": "A → B → C",
          "tiedLeaders": [
            "A"
          ]
        },
        {
          "criterion": "Execution risk",
          "shift": 20,
          "testedWeight": 20,
          "leader": "A",
          "leaderScore": 79.99999999992,
          "originalLeaderRank": 1,
          "ranking": "A → B → C",
          "tiedLeaders": [
            "A"
          ]
        }
      ]
    },
    {
      "title": "Criterion range and normalised weight",
      "columns": [
        {
          "key": "criterion",
          "label": "Criterion",
          "unit": ""
        },
        {
          "key": "direction",
          "label": "Preference",
          "unit": ""
        },
        {
          "key": "weight",
          "label": "Weight",
          "unit": "%"
        },
        {
          "key": "min",
          "label": "Minimum",
          "unit": ""
        },
        {
          "key": "max",
          "label": "Maximum",
          "unit": ""
        }
      ],
      "rows": [
        {
          "criterion": "Capital cost",
          "direction": "Lower is preferred",
          "weight": 99.9999999999,
          "min": 0,
          "max": 2
        },
        {
          "criterion": "Strategic impact",
          "direction": "Higher is preferred",
          "weight": 9.999999999989999e-11,
          "min": 0,
          "max": 100
        },
        {
          "criterion": "Readiness",
          "direction": "Higher is preferred",
          "weight": 0,
          "min": 0,
          "max": 100
        },
        {
          "criterion": "Execution risk",
          "direction": "Lower is preferred",
          "weight": 0,
          "min": 0,
          "max": 100
        }
      ]
    }
  ],
  "warnings": [
    "The preferred alternative changes in a tested weight case. Treat the base ranking as a preference-dependent result."
  ],
  "summary": "A leads with 100 preference points. The first display name remains first in 6 of eight tested weight shifts. 3 alternatives are non-dominated on all four raw criteria. Scores reflect stated preferences and this alternative set.",
  "methods": [
    "Weights are normalised to sum to one. Cost and risk are minimised, impact and readiness maximised.",
    "Each raw criterion maps linearly to 0 to 1 over the current alternative set; equal values receive 0.5.",
    "Weighted score = 100 × sum of normalised weight × normalised criterion value.",
    "A Pareto alternative is not weakly dominated on all four raw criteria with strict dominance on at least one.",
    "Sensitivity shifts each normalised weight by ±20 percentage points, capped at 0 or 100%, and scales other weights proportionally.",
    "Canonical decimal normalisation, contributions, ranking and sensitivity redistribution use exact rational arithmetic. Released weight follows positive supplied weights; equal-thirds redistribution is used only when every other weight is exactly zero.",
    "Tied exact scores use literal name order independent of browser language for consistent display; the model displays every equal leading alternative and implies no strict preference."
  ],
  "limitations": [
    "Compensatory preferences. Scores are not probabilities, returns or forecasts.",
    "Normalisation changes with the alternative set. Scores cannot be compared across changed sets.",
    "No portfolio allocation optimiser, synergy effects or binding budget constraints.",
    "Exact arithmetic concerns the supplied decimal values and preference rule. Numeric chart displays are approximations, and neither measured criteria nor accepted preferences become certain through the computation.",
    "Numerical input precision: use zero or absolute values of at least 0.000000001. Smaller nonzero inputs are rejected explicitly."
  ]
}