PUBLIC-DATASET RESULT

OES-Resilience

NASA SMAP and MSL labeled telemetry anomaly dataset · criterion not met

Interpretation

The stated v0.5 success criterion was not met. OES32 was significantly better than EWMA on SMAP only and was not significantly different from the other baselines; it did not significantly lose to any baseline. Because it did not significantly beat all four baselines on at least one dataset, the criterion fails. maxabs had a numerically higher pooled event F1 on both datasets and CUSUM on MSL, but those differences were not significant.

Run record

Project version
0.5.0 (public evaluation description)
Code version
0.4.0 (saved run metadata; public evaluation described as v0.5.0)
Code commit
Not recorded
Evidence class
public_dataset
Dataset type
public spacecraft telemetry; datasets reported separately
Dataset notes
Primary all-channel results at a 1% train-calibrated false-alarm target: 54 SMAP channels / 68 merged events and 27 MSL channels / 36 events. No raw telemetry is included.
Seed
42
Baselines
maxabs, zscore, ewma, cusum
Protocol
smap-msl-blind-v1 · 1
Protocol lock claim
2026-10-03 (source-stated) (source-stated; not independently time-verified)
Protocol SHA-256
927cf78fe7acc1cdc2a044a800b1e7aef2d954cd7e3b60a5b6b5b31b552b8ea3
Protocol lock commit
fdf99050046a9b1369eb5d2988ff7d5d8563e784
Project source
https://github.com/sparkainlp-x/oes-resilience
Dataset source
https://doi.org/10.1145/3219819.3219845
Source note
The bundled public result files are copied from the linked repository. The saved run metadata reports package version 0.4.0; it does not record the evaluated-code commit.

Reported metrics

Values are copied from the declared run summary. This report does not calculate scores, rank methods, or combine metrics across scopes.

SMAP (all channels; target FP 0.01)

MethodMetricValueUnit95% intervalNote
oes32event precision0.262857fraction——
oes32event recall0.676471fraction——
oes32event F10.378601fraction[0.273556, 0.522167]—
oes32false alarms per 1,000 test samples0.29599alarm runs / 1,000 samples——
maxabsevent precision0.537037fraction——
maxabsevent recall0.426471fraction——
maxabsevent F10.47541fraction[0.328767, 0.645841]—
maxabsfalse alarms per 1,000 test samples0.057362alarm runs / 1,000 samples——
zscoreevent precision0.031878fraction——
zscoreevent recall0.676471fraction——
zscoreevent F10.060887fraction[0.032237, 0.155983]—
zscorefalse alarms per 1,000 test samples3.205408alarm runs / 1,000 samples——
ewmaevent precision0.046047fraction——
ewmaevent recall0.779412fraction——
ewmaevent F10.086957fraction[0.060642, 0.131869]—
ewmafalse alarms per 1,000 test samples2.519354alarm runs / 1,000 samples——
cusumevent precision0.093604fraction——
cusumevent recall0.882353fraction——
cusumevent F10.169252fraction[0.122105, 0.256413]—
cusumfalse alarms per 1,000 test samples1.333101alarm runs / 1,000 samples——

MSL (all channels; target FP 0.01)

MethodMetricValueUnit95% intervalNote
oes32event precision0.316456fraction——
oes32event recall0.694444fraction——
oes32event F10.434783fraction[0.333291, 0.575758]—
oes32false alarms per 1,000 test samples0.732412alarm runs / 1,000 samples——
maxabsevent precision0.5fraction——
maxabsevent recall0.5fraction——
maxabsevent F10.5fraction[0.350868, 0.657143]—
maxabsfalse alarms per 1,000 test samples0.244137alarm runs / 1,000 samples——
zscoreevent precision0.151515fraction——
zscoreevent recall0.694444fraction——
zscoreevent F10.248756fraction[0.177911, 0.389381]—
zscorefalse alarms per 1,000 test samples1.898846alarm runs / 1,000 samples——
ewmaevent precision0.13198fraction——
ewmaevent recall0.722222fraction——
ewmaevent F10.223176fraction[0.126982, 0.423358]—
ewmafalse alarms per 1,000 test samples2.319304alarm runs / 1,000 samples——
cusumevent precision0.391304fraction——
cusumevent recall0.75fraction——
cusumevent F10.514286fraction[0.387097, 0.681319]—
cusumfalse alarms per 1,000 test samples0.569654alarm runs / 1,000 samples——

Limitations

Artifact integrity

All referenced files match their manifest SHA-256 values. This confirms bundle consistency only; it does not establish authorship, timing, provenance authenticity, or measurement validity.

  • artifacts/oes-resilience-v0.5/smap_msl_protocol.json — protocol; SHA-256 927cf78fe7acc1cdc2a044a800b1e7aef2d954cd7e3b60a5b6b5b31b552b8ea3
  • artifacts/oes-resilience-v0.5/smap_msl_results/smap_msl_results.json — results; SHA-256 5263abb0359e1f19ba9da8a6f32e3c5c6e9c788809f929c1c066930facf30f72
  • artifacts/oes-resilience-v0.5/smap_msl_results/smap_msl_summary.csv — summary; SHA-256 ff5de8c39a1bc94791d56e512311fe6e4f49dc372e9e7195236069c531fca2ba
  • artifacts/oes-resilience-v0.5/smap_msl_results/smap_msl_comparisons.csv — comparisons; SHA-256 01c3d5422fe486f4bb771fa9c7eeba0cf0f578b4dad8119c3d02458741a881cc
  • artifacts/oes-resilience-v0.5/smap_msl_results/smap_msl_run_metadata.json — run_metadata; SHA-256 ef7941a5e583fc1d9b35f1a0756eca61c3091b2be60de640b57d954b74a81f78
  • artifacts/oes-resilience-v0.5/smap_msl_results/SHA256SUMS — upstream_checksum_list; SHA-256 ec66c3bf2e774132f36c90fe0783577da8bc5315b2af6ea420645ea3030d37d7

SHA-256 matching proves only byte-for-byte consistency between a referenced file and the digest recorded in this bundle. It does not prove authorship, when a file or protocol existed, provenance authenticity, or measurement or method validity.