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| Autore principale: | |
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| Natura: | Recurso digital |
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| Pubblicazione: |
Zenodo
2025
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| Accesso online: | https://doi.org/10.5281/zenodo.19040358 |
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Sommario:
- A closed-loop system that detects and attempts to correct behavioral drift through a three-level escalation protocol. Across two benchmarks (160 calibrated observations and 157 production calls), 63% of detected drift was classified as UNCORRECTABLE. Claude models show 5-15% correctability vs GPT-instant at 20%, revealing architectural irreversibility.