8.3.Assignment of weights (expert judgment) Relative weights are assigned to each variable to reflect its contribution to the overall state of the system. The weighting is determined through a structured expert judgment process, considering operational experience, historical incident patterns, and the potential severity of energy transfer in the event of a loss of control. 8.4.Calculation of the index The normalized and weighted variables are aggregated to generate a composite indicator called the Integrated Quantum Fatigue Anticipation Threshold (QPIFAT). This index represents the system's potential state with respect to fatigue-related risk, rather than a direct measurement of the probability of incidents occurring. 8.5.Thresholds of interpretation Interpretation bands are defined to support decision-making. These thresholds do not represent absolute safety limits, but rather anticipatory states that indicate an increase in system vulnerability and the need to implement preventive or corrective actions. The threshold values used in this study are for reference and are geared toward the pilot validation phase. 9. PROPOSED APPLICATION (PILOT) In accordance with the WMC 2026 guidelines, the pilot will be implemented in mining operations during the first quarter of 2026. At the time of delivery of this document: ● The pilot project is currently in the design phase. ● No empirical data is available yet. ● The graphs, tables, and results will be incorporated into the final version (before March 2, 2026). Sections reserved for future results ● Tables, graphs, and comparative analysis will be completed with the results after the pilot is finished. 10.EXPECTED IMPACT In general, QPI seeks to add a new layer of anticipation to preventive systems through: ● Early identification of critical configurations. ● Increased sensitivity to unobserved states. ● Better prioritization in operational intervention. ● Reduction of high-potential events (conceptual projection). ● Greater alignment with future mining based on data and complex systems. Specifically, QPIFAT is expected to bring a new layer of anticipation to fatigue management by identifying critical configurations early, better prioritizing interventions, and reducing the risk of high-potential events, aligning with the principles of mining for the future. These estimates will be empirically validated during the pilot phase. 11
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