Deployability reporting audit dataset for "Edge-Device Deployable Self-Supervised Traversability Estimation for Field Robots: A Critical Review"

This dataset contains the per-paper coded indicators from the structureddeployment-constraint reporting audit reported in the review article"Edge-Device Deployable Self-Supervised Traversability Estimation for FieldRobots: A Critical Review." The audit covers the deployability-relevant subset of the surveyed corpus:the union of three thematic populations — segmentation/quantization for edgeneural processing units (Theme 2, 81 papers), self-supervised label generation(Theme 3, 73 papers), and multi-modal sensor fusion under embedded compute(Theme 4, 98 papers) — comprising 252 paper-appearances and 228 unique papersafter deduplication. Each paper was coded for whether it reports fourdeployment constraints: power envelope, thermal behaviour under sustainedload, quantization-induced accuracy degradation, and edge-hardware inferencelatency. Files:- meta_theme2.csv: per-paper coded indicators, Theme 2 (segmentation/quantization).- meta_theme3.csv: per-paper coded indicators, Theme 3 (self-supervised labels).- meta_theme4.csv: per-paper coded indicators, Theme 4 (multi-modal fusion).- meta_extraction_summary.md: aggregate counts, per-theme breakdowns, and the headline reporting rates, with the audit's coding rules and limitations.- README.txt: column definitions, methodology, and citation guidance. Coding was conservative (ambiguous cases scored negative), which biases thereported rates downward. See Sections 2.2 and 8.1 of the article for fullmethodology.