{"graphSha256":"f29d7b1eedeb88387238d2abda347f810d2179c5fdbead47c3ef48507ab20ca5","node":{"id":"N1221","type":"ficha","title":"Field Notes","url":"https://dakleyer.github.io/perspective-beyond/sources/field-notes-n1221/","original":"https://jubap.net/field-notes/","aliases":[],"clusters":["net"],"tags":["decision","movilidad","navegacion"],"summary":"","commit":null,"sourcePath":null,"commitUrl":null,"documentId":"doc-cc6df9a3816b4db102","tagWeights":{"decision":0.3334,"movilidad":0.3333,"navegacion":0.3333},"reading":"A practical logistics system can calculate thousands or millions of technical possibilities while still leaving the most important decision to people: which competing operational objectives deserve priority. xSeil combined a reusable library of feasible route structures, scenario-dependent mathematical scoring, human selection of acceptable trade-offs, and iterative allocation that recalculated the consequences of each commitment. The result was an operational decision architecture connecting planning, vehicle resources, passengers and real-world execution.","readingSource":{"url":"https://jubap.net/field-notes/","section":"Abstract","observed":"2026-11-04","sourceSha256":"52a386942c517df87258056d1497d6321df417533c98be202017b890385dd20c"},"readingSummary":"A practical logistics system can calculate thousands or millions of technical possibilities while still leaving the most important decision to people: which competing operational objectives deserve priority.","contextTokens":154},"relations":[]}