DER Re-Encoding Protocol Specification v1.0: California DMV Autonomous Vehicle Disengagement Corpus 2021–2025

Pre-registration specification for DER re-encoding of the California DMV autonomous vehicle disengagement report corpus (2021–2025). Specifies: (1) source-only constraint governing all re-encoding decisions; (2) purposive stratified sampling design (Pilot-30, three strata); (3) field-by-field re-encoding rules for all six LFP-0 DER fields (F1–F6); (4) U-code master list (9 pre-specified gap codes); (5) H-score computation procedure; (6) event selection log, annotation log, and blinding protocol. This document is archived prior to any data collection or re-encoding activity to establish methodological integrity evidence for peer review. Indexed in the project Root Index (https://doi.org/10.5281/zenodo.17992916). Author: Hon Bor So ORCID: 0009-0008-2768-7494 Author note: The author also publishes under the name Sing So (Chöndrel Dorje).

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-16
DOI
https://doi.org/10.5281/zenodo.19053780
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
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article

DER Re-Encoding Protocol Specification v1.0: California DMV Autonomous Vehicle Disengagement Corpus 2021–2025

Hon Bor So
Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
article

DER Re-Encoding Protocol Specification v1.0: California DMV Autonomous Vehicle Disengagement Corpus 2021–2025

Hon Bor So
article en

Abstract

Pre-registration specification for DER re-encoding of the California DMV autonomous vehicle disengagement report corpus (2021–2025). Specifies: (1) source-only constraint governing all re-encoding decisions; (2) purposive stratified sampling design (Pilot-30, three strata); (3) field-by-field re-encoding rules for all six LFP-0 DER fields (F1–F6); (4) U-code master list (9 pre-specified gap codes); (5) H-score computation procedure; (6) event selection log, annotation log, and blinding protocol. This document is archived prior to any data collection or re-encoding activity to establish methodological integrity evidence for peer review. Indexed in the project Root Index (https://doi.org/10.5281/zenodo.17992916). Author: Hon Bor So ORCID: 0009-0008-2768-7494 Author note: The author also publishes under the name Sing So (Chöndrel Dorje).

Zenodo (CERN European Organization for Nuclear Research)
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Adversarial Robustness in Machine Learning
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