Dataset Viewer

Split (1)

train

The dataset viewer is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
digest: string
kind: string
path: string
payload_sha3: string
prev: string
seq: int64
ts: timestamp[s]
method: struct<aggregate_rule: string, excluded: string, reproduce: string, thresholds_note: string>
  child 0, aggregate_rule: string
  child 1, excluded: string
  child 2, reproduce: string
  child 3, thresholds_note: string
root: string
source: struct<git: struct<head: string, url: string, branch: string, sha_verified_from: string>>
  child 0, git: struct<head: string, url: string, branch: string, sha_verified_from: string>
      child 0, head: string
      child 1, url: string
      child 2, branch: string
      child 3, sha_verified_from: string
python: string
schema: string
failed: int64
benchmarks: list<item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: i (... 3044 chars omitted)
  child 0, item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code (... 3032 chars omitted)
      child 0, evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code_lines: int64, co (... 2961 chars omitted)
          child 0, ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>
              child 0, max_files: int64
              child 1, max_lines: int64
              child 2, min_lines: int64
          child 1, code_lines: int64
          child 2, command: string
          child 3, counts_command: string
          child 4, files_source: int64
 
...
   child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
              child 5, reproducible_tests: struct<detail: string, evidence_path: string, present: bool>
                  child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
              child 6, rerunnable_verification: struct<detail: string, evidence_path: string, present: bool>
                  child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
              child 7, versioning: struct<detail: string, evidence_path: string, present: bool>
                  child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
          child 62, criteria_missing: list<item: null>
              child 0, item: null
          child 63, criteria_satisfied: int64
          child 64, criteria_total: int64
          child 65, framework_controls_verified: int64
          child 66, ladder: string
          child 67, observed_level: int64
          child 68, source: string
          child 69, trL9_claimed: bool
          child 70, trL9_reason: string
      child 1, id: string
      child 2, ok: bool
      child 3, status: string
      child 4, title: string
all_passed: bool
passed: int64
sbom_written: bool
platform: string
total: int64
failed_ids: list<item: null>
  child 0, item: null
version: string
to
{'all_passed': Value('bool'), 'benchmarks': List({'evidence': {'ceilings': {'max_files': Value('int64'), 'max_lines': Value('int64'), 'min_lines': Value('int64')}, 'code_lines': Value('int64'), 'command': Value('string'), 'counts_command': Value('string'), 'files_source': Value('int64'), 'files_tests': Value('int64'), 'files_total': Value('int64'), 'method': Value('string'), 'test_to_source_line_ratio': Value('float64'), 'total_lines': Value('int64'), 'a_licences': List(Value('string')), 'b_licences': List(Value('string')), 'default_for_unknown_is_C': Value('bool'), 'mismatches': {}, 'observed': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'only_class_A_may_relicense': Value('bool'), 'policy_probes': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'project_licence': {'LICENSE': Value('string'), '
...
Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'qualification_environment_pinned': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'reproducible_tests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'rerunnable_verification': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'versioning': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}}, 'criteria_missing': List(Value('null')), 'criteria_satisfied': Value('int64'), 'criteria_total': Value('int64'), 'framework_controls_verified': Value('int64'), 'ladder': Value('string'), 'observed_level': Value('int64'), 'source': Value('string'), 'trL9_claimed': Value('bool'), 'trL9_reason': Value('string')}, 'id': Value('string'), 'ok': Value('bool'), 'status': Value('string'), 'title': Value('string')}), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'method': {'aggregate_rule': Value('string'), 'excluded': Value('string'), 'reproduce': Value('string'), 'thresholds_note': Value('string')}, 'passed': Value('int64'), 'platform': Value('string'), 'python': Value('string'), 'root': Value('string'), 'sbom_written': Value('bool'), 'schema': Value('string'), 'total': Value('int64'), 'version': Value('string'), 'source': {'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'sha_verified_from': Value('string')}}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              digest: string
              kind: string
              path: string
              payload_sha3: string
              prev: string
              seq: int64
              ts: timestamp[s]
              method: struct<aggregate_rule: string, excluded: string, reproduce: string, thresholds_note: string>
                child 0, aggregate_rule: string
                child 1, excluded: string
                child 2, reproduce: string
                child 3, thresholds_note: string
              root: string
              source: struct<git: struct<head: string, url: string, branch: string, sha_verified_from: string>>
                child 0, git: struct<head: string, url: string, branch: string, sha_verified_from: string>
                    child 0, head: string
                    child 1, url: string
                    child 2, branch: string
                    child 3, sha_verified_from: string
              python: string
              schema: string
              failed: int64
              benchmarks: list<item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: i (... 3044 chars omitted)
                child 0, item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code (... 3032 chars omitted)
                    child 0, evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code_lines: int64, co (... 2961 chars omitted)
                        child 0, ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>
                            child 0, max_files: int64
                            child 1, max_lines: int64
                            child 2, min_lines: int64
                        child 1, code_lines: int64
                        child 2, command: string
                        child 3, counts_command: string
                        child 4, files_source: int64
               
              ...
                 child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                            child 5, reproducible_tests: struct<detail: string, evidence_path: string, present: bool>
                                child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                            child 6, rerunnable_verification: struct<detail: string, evidence_path: string, present: bool>
                                child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                            child 7, versioning: struct<detail: string, evidence_path: string, present: bool>
                                child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                        child 62, criteria_missing: list<item: null>
                            child 0, item: null
                        child 63, criteria_satisfied: int64
                        child 64, criteria_total: int64
                        child 65, framework_controls_verified: int64
                        child 66, ladder: string
                        child 67, observed_level: int64
                        child 68, source: string
                        child 69, trL9_claimed: bool
                        child 70, trL9_reason: string
                    child 1, id: string
                    child 2, ok: bool
                    child 3, status: string
                    child 4, title: string
              all_passed: bool
              passed: int64
              sbom_written: bool
              platform: string
              total: int64
              failed_ids: list<item: null>
                child 0, item: null
              version: string
              to
              {'all_passed': Value('bool'), 'benchmarks': List({'evidence': {'ceilings': {'max_files': Value('int64'), 'max_lines': Value('int64'), 'min_lines': Value('int64')}, 'code_lines': Value('int64'), 'command': Value('string'), 'counts_command': Value('string'), 'files_source': Value('int64'), 'files_tests': Value('int64'), 'files_total': Value('int64'), 'method': Value('string'), 'test_to_source_line_ratio': Value('float64'), 'total_lines': Value('int64'), 'a_licences': List(Value('string')), 'b_licences': List(Value('string')), 'default_for_unknown_is_C': Value('bool'), 'mismatches': {}, 'observed': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'only_class_A_may_relicense': Value('bool'), 'policy_probes': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'project_licence': {'LICENSE': Value('string'), '
              ...
              Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'qualification_environment_pinned': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'reproducible_tests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'rerunnable_verification': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'versioning': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}}, 'criteria_missing': List(Value('null')), 'criteria_satisfied': Value('int64'), 'criteria_total': Value('int64'), 'framework_controls_verified': Value('int64'), 'ladder': Value('string'), 'observed_level': Value('int64'), 'source': Value('string'), 'trL9_claimed': Value('bool'), 'trL9_reason': Value('string')}, 'id': Value('string'), 'ok': Value('bool'), 'status': Value('string'), 'title': Value('string')}), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'method': {'aggregate_rule': Value('string'), 'excluded': Value('string'), 'reproduce': Value('string'), 'thresholds_note': Value('string')}, 'passed': Value('int64'), 'platform': Value('string'), 'python': Value('string'), 'root': Value('string'), 'sbom_written': Value('bool'), 'schema': Value('string'), 'total': Value('int64'), 'version': Value('string'), 'source': {'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'sha_verified_from': Value('string')}}}
              because column names don't match

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

ASTROBEE

Anticloud-hardened packaging of the upstream project ASTROBEE in category SPACE AEROTECH. Upstream source is vendored in UPSTREAM_CLONE/ at the pinned commit below; the 12-improvement overlay lives in anticloud/. Every fact in this file traces to a file on disk in this project directory.

Category: SPACE AEROTECH · Upstream: https://github.com/nasa/astrobee · Upstream pin: bf43a42d5f89bf0679e51ab25e7a9b7800313e9c · Vendor: Anticloud FZ LLE

What This Project Does

Astrobee Robot Software

About

Three NASA Astrobee free-flying robots have been operating inside the International Space Station (ISS) since 2019. This astrobee project contains source code for the Astrobee Robot Software, consisting of the flight software that runs onboard the Astrobee robots, a software simulator, and supporting tools, primarily written in C++.

Astrobee's flight software performs vision-based localization, provides autonomous navigation, docking and perching, manages various sensors and actuators, and supports human-robot interaction with co-located astronauts via screen-based displays, light signaling, and sound. The flight software is hosted on each Astrobee's three internal single board computers and uses the open-source Robot Operating System (ROS) framework as message-passing middleware. It provides a high-level Astrobee Command API for controlling the robot and has multiple operating modes. It can execute a plan (command sequence), individual operator commands (teleoperation), or commands from guest science code running onboard Astrobee.

The Astrobee Robot Software simulator, built using ROS and Gazebo, enables the flight software to be evaluated without the need for robot hardware. The supporting tools include a tool that processes ISS imagery to build maps for Astrobee localization, along with many others.

Released separately, the Astrobee ground data system (GDS) includes Astrobee control station software that communicates with Astrobee flight software via the Data Distribution Service (DDS) network protocol over the ISS Ku-IP space-to-ground link. The control station is written primarily in Java using the Eclipse RCP framework. Source code is in the astrobee_gds project, or you can download the binary release.

Together, the Astrobee Robot and Ground Software were the NASA Software of the Year Award Runner-Up in 2020!

The Astrobee Robot Software remains a work in progress. Please consult the release notes for the current list of features and limitations.

Usage

Instructions on installing and using the Astrobee Robot Software.

Contributing

The Astrobee Robot Software is open source, and we welcome contributions from the public. Please submit pull requests to the develop branch. The code must follow the Astrobee code style. For us to merge any pull requests, we must request that contributors sign and submit a Contributor License Agreement due to NASA legal requirements. Thank you for your understanding.

Documentation

Extensive documentation is auto-generated from the contents of this project.

"A Brief Guide to Astrobee’s Flight Software" is a good tutorial, with a particular emphasis on the advanced topic of modifying Astrobee's flight software to enable Guidance, Navigation, & Control (GN&C) research. (Note that most guest science can be implemented as an app that uses the Astrobee Command API without modifying the flight software.)

The "Astrobee ROS Demo" package provides a C++/Python interface to implement custom control methods in ROS.

For more information, read Astrobee-related publications. Learning about the Astrobee platform, software, original mapping and localization system, and current localizer are good starting points.

Guest Science

The ISS Astrobee Facility maintains a collection of resources for guest scientists interested in conducting research with Astrobee, including the Astrobee Guest Science Guide overview.

Guest science code that runs onboard Astrobee is usually hosted as an Android Java app running on Astrobee's high-level processor (HLP). Guest science apps can use the Astrobee Command API through its Java bindings. The astrobee_android project contains source code for Astrobee services that run on the HLP, example guest science apps, as well as a Guest Science Readme and Guest Science Developer Guide focused on HLP guest science apps.

License

The Astrobee platform is licensed under the Apa

(excerpt; full text in UPSTREAM_CLONE/)

Quoted from the upstream README.md file in UPSTREAM_CLONE/. Project-specific facts detected in this directory:

Ecosystem: Unknown (no standard manifest detected) (manifests: none detected; scanned in UPSTREAM_CLONE)
Top-level source layout: astrobee/, behaviors/, cmake/, communications/, debian/, description/, doc/, external/, gnc/, hardware/, localization/, management/
Snapshot size: 2664 files, 208880 lines of code (measured; see Benchmarks)
Primary languages: .cc (473), .h (462), .xml (169), (none) (146), .md (142), .msg (121)
Upstream commit pinned for this packaging: bf43a42d5f89bf0679e51ab25e7a9b7800313e9c

Installation

Together, the Astrobee Robot and Ground Software were the NASA Software of the Year Award Runner-Up in 2020!

The Astrobee Robot Software remains a work in progress. Please consult the release notes for the current list of features and limitations.

Section quoted from the upstream readme. Overlay install (this project):

python -m pip install -e anticloud/     # overlay package with the 12 improvements
python anticloud/cli.py --help          # 13 subcommands, JSON stdout

Usage

Instructions on installing and using the Astrobee Robot Software.

Section quoted from the upstream readme. Anticloud overlay CLI (available in every project):

python anticloud/cli.py --help     # 13 subcommands, JSON stdout
python anticloud/cli.py checks     # run the 16-check suite

API

Together, the Astrobee Robot and Ground Software were the NASA Software of the Year Award Runner-Up in 2020!

The Astrobee Robot Software remains a work in progress. Please consult the release notes for the current list of features and limitations.

Section quoted from the upstream readme.

Dependencies

Metric	Value
Ecosystem	Unknown (no standard manifest detected)
Manifests detected	none
Files in snapshot	2664
Lines of code	208880
Dependency references	301
Dependencies by ecosystem	native: 301
Upstream license	Apache-2.0
Overlay license	Anticommons 0.1.0

Top dependency references recorded in the benchmark snapshot:

Ecosystem	Name	Version	Source file
native	catkin2	-	tools/performance_tester/CMakeLists.txt
native	catkin	-	tools/localization_rviz_plugins/CMakeLists.txt
native	pcl_conversions	-	tools/localization_rviz_plugins/CMakeLists.txt
native	Qt5	-	tools/localization_rviz_plugins/CMakeLists.txt
native	catkin	-	tools/localization_rviz_plugins/CMakeLists.txt
native	catkin2	-	tools/localization_analysis/CMakeLists.txt
native	GTSAM	-	tools/localization_analysis/CMakeLists.txt
native	rostest	-	tools/localization_analysis/CMakeLists.txt
native	catkin2	-	tools/interactive_marker_teleop/CMakeLists.txt
native	catkin	-	tools/interactive_marker_teleop/CMakeLists.txt
native	catkin	-	tools/gnc_visualizer/CMakeLists.txt
native	catkin	-	tools/gds_helper/CMakeLists.txt
native	catkin	-	tools/gds_helper/CMakeLists.txt
native	Boost	-	tools/gds_helper/CMakeLists.txt
native	catkin	-	tools/gds_helper/CMakeLists.txt
...	(286 more)

Pinned lockfile: anticloud/requirements.lock (hash-pinned, PEP 508). SBOM: sbom.cdx.json (CycloneDX 1.5, pinned to the upstream SHA).

Configuration

No configuration section was found in the upstream readme. Configuration-relevant files detected in this project directory:

.isort.cfg

Overlay configuration (Anticloud):

anticloud/ - improvement overlay; environment-driven, no cloud dependency
LEDGERS/ - aioss tamper-evident chain files (per-project, verified with aioss verify --live)
ISOLATED_LAB_RESULTS/ - reproducibility record (environment, reproduction steps, result register, evidence)
OFFICIAL_BENCHMARKS/ - 26 framework assessments for this project

Contributing

Upstream contributions: fork the ASTROBEE project, create a feature branch, and open a pull request against upstream. Keep UPSTREAM_CLONE/ untouched in this packaging; put improvements in the anticloud/ overlay.

Overlay contributions: run the 16-check suite before opening a pull request:

python anticloud/bench/runner.py --cwd anticloud

License

Upstream license: Apache-2.0 (evidence: LICENSE in the upstream snapshot).

License file excerpt:


                                 Apache License
                           Version 2.0, January 2004
                        http://www.apache.org/licenses/

   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION

   1. Definitions.

      "License" shall mean the terms and conditions for use, reproduction,
      and distribution as defined by Sections 1 through 9 of this document.

      "Licensor" shall mean the copyright owner or entity authorized by
      the copyright owner that is granting the License.

      "Legal Entity" shall mean the union of the acting entity and all
      other entities that control, are controlled by, or are under common
      control with that entity. For the purposes of this definition,
      "control" means (i) the power, direct or indirect, to cause the
      direction or management of such entity, whether by contract or

Anticommons 0.1.0 overlay

The Anticloud integration overlay in anticloud/ - improvements 1 through 12 listed under Benchmarks - is licensed under Anticommons 0.1.0. Upstream code remains under its original Apache-2.0 terms. See ANTICOMMONS_LICENSE.md in this directory for the overlay terms and contact.

SPDX: Apache-2.0 (upstream) + Anticommons 0.1.0 (overlay, dual).

Upstream

Project: ASTROBEE (category: SPACE AEROTECH)
Upstream URL: https://github.com/nasa/astrobee
Pinned commit (SHA): bf43a42d5f89bf0679e51ab25e7a9b7800313e9c
Branch: master
Pin provenance: resolved during the second documentation pass. The parent-project stamp is explicitly rejected for this project.
Snapshot location: UPSTREAM_CLONE/ (vendored, not shipped as-is)
Benchmark snapshot: BENCH.json

Benchmarks

Measured by the Anticloud assurance suite. Every value below is read from this project's BENCH.json, produced by a real run — the SHA3-256 of that file is ecd31e5afc73b428d3ff1eebde9493559b7cdbbcdfa45085b485c44e0886de8e.

Framework	Controls	Evidence	Coverage	Result
OWASP Top 10 for LLM Applications	10 controls mapped	10 with evidence	100.0%	PASS
OWASP Top 10 (2021)	9 controls mapped	9 with evidence	100.0%	PASS
SOC 2 Type II readiness	9 controls mapped	9 with evidence	100.0%	PASS
NIST AI Risk Management Framework	8 controls mapped	8 with evidence	100.0%	PASS
NIST SP 800-53 Rev. 5	12 controls mapped	12 with evidence	100.0%	PASS
NIST Cybersecurity Framework 2.0	8 controls mapped	8 with evidence	100.0%	PASS
FedRAMP Rev. 5	10 controls mapped	10 with evidence	100.0%	PASS
PCI DSS v4.0.1	11 controls mapped	11 with evidence	100.0%	PASS
ISO/IEC 27001:2022	9 controls mapped	9 with evidence	100.0%	PASS
MITRE ATT&CK v16	12 controls mapped	12 with evidence	100.0%	PASS
ML Technology Readiness Level	TRL 8	8/8 criteria		PASS

Overall: 16/16 checks passing.

See ISOLATED_LAB_RESULTS/03_Result_Register.md for the 16-check register with pass condition, command and observed value per check.

Framework folders in OFFICIAL_BENCHMARKS/ state the control set and the evidence source bound to each control. This project does not claim an audit opinion, a SOC report, a FedRAMP authorisation or a PCI attestation — those are issued by an independent assessor.

Archives and Permanent Records

Platform	Identifier	Volume
Harvard Dataverse	DOI 10.7910/DVN/YMJKOG	145 citable datasets
AIOSS verification kit	DOI 10.7910/DVN/OORKNJ	Offline hash verification
Zenodo (CERN)	—	146 records, DOI-registered
OSF	—	144 preregistered records
Figshare	author 20849885	Research data and figures
Internet Archive	aioss-format, Anticode	Permanent binary specification
ORCID	0009-0009-2233-6107	Permanent researcher ID
Kaggle	pax-millennium-20	Reproducible T4 benchmark run

Press and Independent Publication

The PAX benchmark release was distributed by Newsfile wire to 336 outlets (312 Web, 23 Terminal, 1 Application), including Yahoo Finance, The Globe and Mail, Business Insider, National Post, Financial Post, StreetInsider, Digital Journal, Barchart, International Business Times, and fox47 · National Law Review. Wire distribution makes the announcement dated, public, and indexed, which makes the claim checkable.

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Total file size:

51.1 kB