Final decisionFrequency of extreme lowsIt measures cold risk by frequency and stage, not by isolated data.Origin: Yolia's safe educational catalogExact route: /biblioteca?ruta=decision/reglas/min_temp_frequency FULL TOPICFrequency of extreme lows Name and classification of the rule Frequency of extreme minimums. Final Decision sheet documenting this rule of the climate and climate-history category, with high severity, part of the complete catalog of Final Decision rules Yolia reviews before approving any formula generated for an actual case within the system. What this rule is within the catalog It's the entry that explains the "Frequency of extreme minimums" rule: It measures cold risk by frequency and stage, not by an isolated data point. This rule is part of the climate and climate-history category within Yolia's complete Final Decision catalog that Yolia reviews in every analyzed case. What exactly this rule evaluates This rule specifically evaluates whether the climate and climate history data is present and sufficient for the decision engine to proceed with confidence, being classified as high severity within the system's complete catalog of Final Decision rules. Why it matters within the complete process It is key because it measures cold risk by frequency and stage, not by an isolated data point. Without this verified data or condition, the rest of the analysis within the case loses precision and the decision engine cannot sustain the confidence level it declares to the user in the final formula delivered. Easy explanation It measures cold risk by frequency and stage, not by an isolated data point. Yolia checks this point before trusting a decision. If important information is missing, Yolia must lower confidence or stop instead of inventing, explained in simple language for anyone new to the topic. Intermediate explanation It measures cold risk by frequency and stage, not by an isolated data point. This rule works as a gate: it changes which alternatives remain reasonable and which data is worth obtaining next. A decision changes when the crop, the stage, the environment, or the data quality changes. Advanced explanation It measures cold risk by frequency and stage, not by an isolated data point. The rule takes part in a validation chain with identity, context, phenology, evidence, compatibility, biological capacity, and safety limits. The reason for acceptance/blocking is explained without publishing weights. Mechanism behind this rule The mechanism behind this rule is that the decision engine compares the reported climate and climate history data against the required minimum threshold, blocking or warning according to the high severity declared for this rule within the system's complete catalog. When and where this rule applies This rule applies within the climate and climate-history category of the Final Decision catalog, being mandatory in every case, regardless of the species or particular context being analyzed at that moment within Yolia's complete system. What other rules or engines it relates to It relates to the rest of the rules in the climate and climate history category and to the Audit Engine, which verifies that all the catalog's mandatory rules have been met before approving the final formula generated for the case being analyzed. Relevant differences between species in the catalog The principle of this rule is identical for the catalog's 4 species; what changes is the specific threshold or tolerance for climate and climate history depending on the particular species being treated within the case being analyzed at that point in the complete process. How it is observed in practice on a case In practice, this is observed when the system reviews the climate and climate history data reported for the case and decides whether to proceed with full confidence, lower its confidence level, or halt the process until the missing data is obtained for the case being analyzed. What happens if this rule is ignored If this rule is ignored, the engine could proceed with a formula based on incomplete or missing climate and climate history data, increasing the risk of delivering a less accurate or outright wrong recommendation for the actual case being analyzed. How Yolia uses it within the process Yolia uses this as part of the validation chain it reviews before approving a formula, applying this high-severity rule in both pilot mode and final mode, though with a different tolerance level depending on the case's active mode, part of the structured process the system follows. Common interpretation mistakes Thinking that this rule is just an administrative formality — in reality it measures cold risk by frequency and stage, not by an isolated data point, which makes it a real condition that directly affects the quality of the final formula delivered to the user within the case being analyzed. Evidence and limits of current knowledge Its specification acknowledges that the exact threshold that triggers this rule can vary depending on the reported context, without publishing the internal weights or the exact private thresholds, leaving room for this logic to continue being refined within Yolia's system. Related topics and rules Climate and climate history, related topic — Audit Engine, related engine — Pilot/final gate, related entry within Yolia's complete Final Decision catalog for the process, see also the directly related rules and engines.