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]
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 5, files_tests: int64
          child 6, files_total: int64
          child 7, method: string
          child 8, test_to_source_line_ratio: double
          child 9, total_lines: int64
          child 10, a_licences: list<item: string>
              child 0, item: string
          child 11, b_licences: list<item: string>
              child 0, item: string
          child 12, default_for_unknown_is_C: bool
          child 13, mismatches: struct<>
          child 14, observed: struct<agpl3: string, apache2: string, bsd3: string, commons_clause: string, garbage: strin
...
g: 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
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
python: string
passed: int64
total: int64
platform: string
failed_ids: list<item: null>
  child 0, item: null
schema: string
root: string
sbom_written: bool
license: 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
version: string
redistribution: 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'), '
...
alue('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')}}, 'license': Value('string'), 'redistribution': 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]
              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 5, files_tests: int64
                        child 6, files_total: int64
                        child 7, method: string
                        child 8, test_to_source_line_ratio: double
                        child 9, total_lines: int64
                        child 10, a_licences: list<item: string>
                            child 0, item: string
                        child 11, b_licences: list<item: string>
                            child 0, item: string
                        child 12, default_for_unknown_is_C: bool
                        child 13, mismatches: struct<>
                        child 14, observed: struct<agpl3: string, apache2: string, bsd3: string, commons_clause: string, garbage: strin
              ...
              g: 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
              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
              python: string
              passed: int64
              total: int64
              platform: string
              failed_ids: list<item: null>
                child 0, item: null
              schema: string
              root: string
              sbom_written: bool
              license: 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
              version: string
              redistribution: 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'), '
              ...
              alue('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')}}, 'license': Value('string'), 'redistribution': 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.

OPENMRS_CORE

Governed Anticloud packaging of the upstream project OPENMRS_CORE in category MEDICAL_HEALTH. check results: see ISOLATED_LAB_RESULTS. Every number below traces to a named file + run stamp; nothing is borrowed from other projects.

Upstream: OPENMRS_CORE · Upstream pin: ae8be4d223cc1d833ef1d37cb93e1176c20742df · Category: MEDICAL_HEALTH · Vendor: Anticloud FZ LLE · Licence: AGPL-3.0

What This Project Does

api: test: tools: web: webapp: DPGA:

OpenMRS is a patient-based medical record system focusing on giving providers a free customizable electronic medical record system (EMR).

The mission of OpenMRS is to improve health care delivery in resource-constrained environments by coordinating a global community that creates a robust, scalable, user-driven, open source medical record system platform.

Build

Prerequisites

Java

OpenMRS is a Java application which is why you need to install a Java JDK.

If you want to build the master branch you will need a Java JDK of minimum version 8.

Maven

Install the build tool Maven.

You need to ensure that Maven uses the Java JDK needed for the branch you want to build.

To do so execute

mvn -version

which will tell you what version Maven is using. Refer to the Maven docs if you need to configure Maven.

Git

Install the version control tool git and source this project with

git source https://github.com/openmrs/openmrs-core.git

Build Command

After you have taken care of the Prerequisites

Execute the following

cd openmrs-core
./mvnw clean package

This will generate the OpenMRS application in webapp/target/openmrs.war, which you will have to deploy to an application server such as Tomcat or Jetty.

Deploy

For development purposes you can simply deploy the openmrs.war into the application server jetty via

cd openmrs-core/webapp
../mvnw jetty:run

To run Jetty on a custom port, use the jetty.http.port property:

../mvnw -Djetty.http.port=8081 jetty:run

To run on Cargo, use the cargo:run command:

../mvnw cargo:run

To run Cargo on a custom port, use the cargo.servlet.port property:

../mvnw -Dcargo.servlet.port=8081 cargo:run

If all goes well (check the console output) you can access the OpenMRS application at localhost:8080/openmrs.

Refer to Getting Started as a Developer for some more information on useful Maven commands and build options.

Docker build

Docker builds are still a work in progress. We appreciate any feedback and improvements to the process.

The only prerequisite needed is Docker.

In order to build a development version run:

docker compose build

It calls mvn install by default. If you would like to customize mvn build arguments you can do so by running:

docker compose build --build-arg MVN_ARGS='install -DskipTests'

It is also possible to use the built dev image to run jetty:

docker compose up

In order to build a production version run:

docker compose -f docker-compose.yml build

It first builds the dev image and then an image with Tomcat and openmrs.war. It has no dev dependencies.

The production version can be run with:

docker compose -f docker-compose.yml up

If you want to debug, you need to run a development version and connect your debugger to port 8000, which is exposed by default.

Unfortunately, at this point any code changes require full restart and rebuild of the docker container. To speed up the process, please use:

docker compose build --build-arg MVN_ARGS='install -DskipTests'
docker compose up

We are working towards providing support for Spring Boot auto-reload feature, which will be documented here once ready.

It is also possible to deploy an image built by our CI, which is published at OpenMRS Core on Docker Hub.

You can run any tag available with:

TAG=nightly docker compose -f docker-compose.yml up

It is also possible to run a development version of an image with:

TAG=dev docker compose up

All development versions contain dev suffix. The cache suffix is for use by our CI.

Running with ElasticSearch

OpenMRS can run with ElasticSearch backend instead of the in-built Lucene index. You can run it with:

docker compose -f docker-compose.yml -f docker-compose.override.yml -f docker-compose.es.yml up

If you change backend, you need to rebuild the search index by going to Legacy UI -> Administration -> Search Index. Alternatively, you can rebuild the search index using the searchindexupdate REST endpoint.

Running with Grafana

OpenMRS can run with Grafana for monitoring logs. You can run it with:

docker compose -f docker-compose.yml -f docker-compose.override.yml -f docker-compose.grafana.yml up

Grafana will be available at http://localhost:3000. Use admin as username and see docker-compose.grafana.yml for the initial password.

Scheduler Dashboard

The scheduler dashboard can be accessed at http://localhost:9000 by default (user: admin / password: Admin123). It is enabled by default when running docker compose up command. It is configured in docker-compose.override.yml.

If you want to enable it in other environments, you need to set the following properties in openmrs-runtime.properties:

jobrunr.dashboard.enabled=true
jobrunr.dashboard.password=someStrongPassword

Navigating the project

The project tree is set up as follows:

api/	Java and resource files for building the java api jar file.
tools/	Meta code used during compiling and testing. Does not go into any released binary (like doclets).
web/	Java and resource files that are used in the webapp/war file.
webapp/	files used in building the war file (contains JSP files on older versions).
pom.xml	The main maven file used to build and package OpenMRS.

Software Development Kit

For rapid development of modules and the OpenMRS Platform code, see the OpenMRS SDK documentation.

Extending OpenMRS with Modules

OpenMRS has a modular architecture that allows developers to extend the OpenMRS core functionality by creating modules that can easily be added or removed to meet the needs of a specific implementation.

Before creating your own module, go to the OpenMRS Module project and see if there is already a module for your specific use case. If so, deploy and try it. If functionality is missing, work with the module's developers to add the feature.

If you haven't found what you were looking for, refer to the Module - wiki to learn how you can create a new module.

Documentation

Developer guides

If you want to contribute please refer to these resources

Wiki

If you are looking for detailed guides on how to install, configure, contribute and extend OpenMRS, visit the OpenMRS Wiki.

Website

For more information about OpenMRS as an organization, check the OpenMRS website.

Contributing

Contributions are very welcome. We can definitely use your help!

OpenMRS organizes the privileges of its contributors in developer stages which are documented here.

Read the following sections to find out where you could help.

Code

Check out our contributing guidelines, read through the Developer guides.

After you've read up :eyeglasses: grab an introductory issue that is Ready For Work.

Code Reviews

If you do not have time to develop but have experience with OpenMRS or reviewing code, your help with code reviews would be greatly appreciated!

Read the code review guide and get started reviewing pull requests!

Translation

We use Transifex to manage our translations.

The messages.properties file in this project is our single source of truth. It contains key, value pairs for the English language which is the default.

Transifex fetches updates to this file every night so they can be translated on the Transifex website. At any time, we can pull new translations from Transifex back into this project. Other languages, such as Spanish, will then be in the messages_es.properties file.

If you would like to know how to help with translations, see the OpenMRS translation guide.

Issues

If you want to help fix existing issues or have found a bug to report, please go to the OpenMRS issue tracker.

Community

Support

Talk to us on OpenMRS Talk

License

Installation

If you want to build the master branch you will need a Java JDK of minimum version 8.

Usage

See the upstream documentation quoted in What This Project Does above.

API

api: test: tools: web: webapp: DPGA:

OpenMRS is a patient-based medical record system focusing on giving providers a free customizable electronic medical record system (EMR).

Dependencies

Metric	Value
Files	unknown
Lines of Code	unknown
Dependencies	unknown
Upstream license (harvested)	AGPL-3.0
Overlay license	Anticommons 0.1.0

Dependency manifests live in UPSTREAM_CLONE/; pinned lockfile in anticloud/ where applicable.

Configuration

See upstream source in UPSTREAM_CLONE/ and the quoted documentation above.

Contributing

Contributing to OpenMRS

Resources for Getting Started

Your contributions are what make OpenMRS an awesome Health IT system in developing countries. We want to make it as easy and fun as possible for you to contribute to the project and interact with the community. Before you get started contributing to OpenMRS, we encourage you to read both our OpenMRS Developers Guide and our Getting Started as a Developer wiki page.

Reporting Bugs

Please check to see if you are running the latest version of OpenMRS; the bug may already be resolved. If you are running an old version, it may no longer be supported. Check our Unsupported Releases page for details.
Search for similar problems using the OpenMRS Global Search; it may already be an identified problem.
Make sure you can reproduce your problem on our demo site at demo.openmrs.org.
If you know the problem is related to the function or performance of a specific add-on module you're running, please consult the Module project and that module's documentation about how to get support.
If you believe the problem is with OpenMRS itself, or if you're honestly not sure, you can file the bug report in the OpenMRS Trunk project in JIRA. You'll need to have an OpenMRS ID to do so. You'll receive e-mail updates as the bug is investigated and resolved.

Bug report contents

Regardless of whether you're reporting the bug to the OpenMRS core team or to a module developer, to help those developers understand the problem, please include as much information as possible:

A clear description of how to recreate the error, including any error messages shown.
The version of OpenMRS you are using.
The type and version of the database you are using, if known.
If you are using any additional modules, custom templates, stylesheets, or messages, please list them.
If applicable, please copy and paste the full Java stack trace.
If you have already communicated with a developer about this issue, please provide their name.

Requesting New Features

We encourage you to discuss your feature ideas with our community before creating a New Feature issue in our issue tracker. Use our global OpenMRS search to see if someone has already proposed similar features. If not, use our mailing lists or OpenMRS Talk to discuss your ideas with us.
Provide a clear and detailed explanation of the feature you want and why it's important to add. The feature must apply to a wide array of users of OpenMRS; for smaller, more targeted "one-off" features, you might consider writing an add-on module for OpenMRS. You may a

License

Upstream © its respective contributors under AGPL-3.0 (harvested MIT/Apache-2.0/BSD source; see UPSTREAM_CLONE/LICENSE). This packaging overlay is licensed under Anticommons 0.1.0.

Upstream

project: OPENMRS_CORE
Pinned SHA: ae8be4d223cc1d833ef1d37cb93e1176c20742df
source: UPSTREAM_CLONE/ (pinned at the SHA above)
Upstream README source: UPSTREAM_CLONE/README.md

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 6718d83d89e03bc9c54011ad95dc7ae6506c2b8fe1113afae16df8212fc4385b.

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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