Dataset registry

Datasets

Data on MedGauge is described evidence first: which capability it serves, which evaluation sets it was checked against, how much was verified by program and by experts, and the identifiability result — then licence and access.

No dataset is published yet. This page describes the method and access tiers that dataset cards will follow.

Types and the capabilities they serve

TypeServesIsolation requirement
Pre-training / mid-training corpusAZero overlap with task statements and answers; canary strings filtered
Evaluation set (closed)A–EHoldout answers never distributed; hash manifest released with the first holdout round
Tuning sets (SFT, preference, verifiable-reward)B, C, DIndependent source material in a separate store; six-dimension similarity check
Trajectory and augmentation setsB, C, D, EProgram-verified and expert-sampled; original records kept; processing map kept with training copies
Environments and rubric librariesB, C, DSnapshot environments versioned; rubric provenance recorded

Access tiers

Open

Direct download under an open licence (for example CC BY 4.0). Only for data that is synthetic or otherwise not personal information.

Research

Application plus a data use agreement: no training on evaluation material, no redistribution, destruction date, incident reporting.

Commercial

By enquiry, after the capability evidence on the card has been reviewed. Not open yet.

Institutional de-identified data is never offered for download at any tier; it is used only inside the evaluation sandbox.

What every dataset card states

  1. Datasheet: motivation, composition, collection, preprocessing, uses, distribution, maintenance.
  2. Relation to benchmarks: capabilities served; evaluation sets isolated from; similarity-check method, result and date.
  3. Provenance: synthetic, public licensed or institutional de-identified; generator version and seed policy; de-identification method; legal status (not personal information, anonymised with an assessment, or de-identified personal information).
  4. Quality: share verified by program; expert-reviewed sample size, sampling method and agreement; identifiability scan result, stated as supporting evidence only.
  5. Format: tasks in the Harbor task format; trajectories as messages + tools + usage, with a mapping to the trajectory format registered in the standards registry (its name and version numbering not yet confirmed by a source check).
  6. Access: tier, licence per tier, DOI, Croissant metadata.

A card with status planned shows a planned banner and no download. Nothing is described as released before it is.

Card dimensions in full

Every dimension below is a field in dataset.schema.json or its datasheet block, validated at build time.

DimensionWhat the card statesWhy it is there
TypePre-training corpus, evaluation set, SFT, preference, trajectory, augmentation, environment or rubric libraryDifferent types carry different isolation duties
Capabilities servedRegistry capability ids the data is meant to improve or measureTies data to the same ids results are reported on
IsolationEvaluation sets checked against; six-dimension similarity method (patient, source, document, template, answer, environment state); result and dateTraining data must not reproduce evaluation material
OriginSynthetic, public licensed, or institutional de-identifiedDetermines legal status and whether download is possible at all
Generator and seedsGenerator version and seed policy for synthetic dataLets a synthetic set be regenerated and audited
De-identificationMethod (identifiers in the 18 Safe Harbor categories, consistent date shifting, technical registration, risk assessment) and assessment referenceDe-identified is not anonymised; the card must say which applies
Legal statusNot personal information, anonymised with an assessment, or de-identified personal informationDecides access tier
Source licencesLicence of every upstream sourceDownstream terms cannot exceed upstream terms
SizeTasks, trajectories, tokensBasic scale
FormatTask format, trajectory format, mapping to an interchange formatReuse without custom parsers
Program verificationShare of items verified by programLabels that a program can check are reported as such
Expert reviewSample size, sampling method, agreement, how error is extrapolatedExpert claims come with their denominator
Identifiability scanScanner coverage and result, labelled as supporting evidence onlyA clean scan is not proof of absence
Intended and excluded usesDatasheet "uses" section, including uses the data must not be put to (for example unvalidated clinical decisions)Responsible reuse
Known limitationsCoverage gaps, population skews, label noise known at releasePrevents over-generalisation
AccessTier, licence per tier, application routeOne place to see who can get what
IdentifiersVersion, DOI, Croissant metadata, citationCitable and machine-readable
MaintenanceMaintainer, update cadence, erratum process, retirementDatasets change; the card says how

Schema: dataset.schema.json. De-identification method: Isolation and the closed set.