datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
pending-medicare-provider-enrollment-data
Pending Medicare Provider Enrollment Data
This is a dated, source-receipted sample of behavioral-health NPIs newly present in CMS's pending first-time Medicare enrollment files on 2026-07-13, compared with the immediately prior 2026-07-09 publication.
Pending does not mean approved. A row indicates that a first-time Medicare enrollment application appeared in a CMS pending file. It does not prove enrollment, credentialing, licensure, a new practice, service availability… See the full description on the dataset page: https://huggingface.co/datasets/unitedideas/pending-medicare-provider-enrollment-data.student-grades-enrollment
University Student Grades & Enrollment Dataset (Free Sample)
This is a free sample with 2,553 rows. The full dataset has 38,567 rows across 5 tables.
Academic records for a simulated mid-size US university (4,200 students) over
6 semesters (Fall 2021 - Spring 2024). Includes student demographics, course
catalog, enrollment records, and grades with realistic GPA distributions.
Features grade inflation trend, prerequisite enforcement, major-specific
performance patterns, and two… See the full description on the dataset page: https://huggingface.co/datasets/mindweave/student-grades-enrollment.clinical-quad-consent-version-drift-reconsent-gap-enrollment-pressure-governance-audit-v0.1Clarus Clinical Quad Coupling Informed Consent Integrity v0.1
PurposeDetect consent integrity failures driven by four interacting nodes.
Quad nodes
Consent version drift or addendum mismatch
Re-consent gap after material risk change
Enrollment pressure or incentives
Governance audit or regulator timing
InputOne vignette.
OutputStrict JSON only.
Required keys
consent_integrity_risk
risk_type
driver_nodes
recommended_action
action_detail
rationale
confidence… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-consent-version-drift-reconsent-gap-enrollment-pressure-governance-audit-v0.1.clinical-quad-enrollment-criteria-drift-site-selection-bias-screening-pressure-v0.1Clarus Clinical Quad Coupling Enrollment Criteria Drift Site Selection Bias Screening Pressure v0.1
PurposeDetect enrollment population drift driven by four interacting nodes.
Quad nodes
Criteria relaxation or documentation gap
Site selection or recruitment bias
Screening workflow pressure
Governance or interim timing pressure
InputOne vignette.
OutputStrict JSON only.
Required keys
enrollment_drift_risk
risk_type
driver_nodes
recommended_action
action_detail
rationale… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-enrollment-criteria-drift-site-selection-bias-screening-pressure-v0.1.clinical-quad-enrollment-protocol-deviation-site-variance-endpoint-integrity-v0.1
Clinical Quad Enrollment–Protocol Deviations–Site Variance–Endpoint Integrity v0.1
What this is
A quad-coupling dataset for trial collapse driven by the interaction of:
enrollment pattern changes
rising protocol deviations
site-to-site variance
endpoint integrity degradation
Task
Input: one quad state rowOutput: label
0 — Stable1 — Drift2 — Collapse
Why it matters
Trials often fail through operational pressure:
recruitment becomes spiky or slow… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-enrollment-protocol-deviation-site-variance-endpoint-integrity-v0.1.clinical-quad-enrollment-protocol-deviation-site-variance-endpoint-integrity-v0.2Clinical Quad Enrollment Protocol Deviation Site Variance Endpoint Integrity v0.2
What this dataset does
It tests whether a model can detect when endpoint integrity degrades under four coupled operational pressures.
Quad nodes
enrollment_pattern
protocol_deviation_rate
site_variance_level
endpoint_integrity
Labels
0 coherent
endpoints clean
enrollment stable
deviations not high
site variance not high
1 tradeoff
strain exists
endpoint softens or system drifts… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-enrollment-protocol-deviation-site-variance-endpoint-integrity-v0.2.clinical-quad-irb-delay-contracting-lag-site-activation-drift-enrollment-shortfall-v0.1Clinical Quad IRB Delay Contracting Lag Site Activation Drift Enrollment Shortfall v0.1
Each row is a site monthly snapshot.
Core quad
IRB delayContracting lagSite activation driftEnrollment shortfall
Target
label_power_loss_next_90d
Files
data/train.csvdata/tester.csvscorer.py
Evaluation
Run model on data/tester.csvReturn predictions row alignedScore with scorer.py
License
MIT
This dataset identifies a measurable coupling pattern associated with systemic instability.
The sample demonstrates… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-irb-delay-contracting-lag-site-activation-drift-enrollment-shortfall-v0.1.IPEDS_ENROLLMENTmanaged-care-enrollment-by-program-and-population
Managed Care Enrollment by Program and Population (Duals)
Description
The Medicaid Managed Care Enrollment Report profiles enrollment statistics on Medicaid managed care programs on a plan-specific level. The managed care enrollment statistics include enrollees receiving comprehensive benefits and limited benefits and are point-in-time counts.
Because Medicaid beneficiaries may be enrolled concurrently in more than one type of managed care program (e.g., a Comprehensive… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/managed-care-enrollment-by-program-and-population.az-school-graduate-enrollment
Azerbaijani School Graduate Enrollment Indicators (1995-2023)
This dataset compiles key enrollment indicators of school graduates from 1995 to 2023, presenting a comprehensive view of their performance in entrance exams and subsequent acceptance into higher education institutions. It includes data on both male and female graduates, offering insights into gender-specific trends and performances. The dataset features a generalized rating system that compares the school graduates'… See the full description on the dataset page: https://huggingface.co/datasets/nijatzeynalov/az-school-graduate-enrollment.monthly-enrollment-test
Monthly Enrollment - Test
Description
All states (including the District of Columbia) are required to provide data to The Centers for Medicare & Medicaid Services (CMS) on a range of Medicaid and Children’s Health Insurance Program (CHIP) indicators related to key application, eligibility, enrollment and call center processes. These data reflect enrollment activity for all populations receiving comprehensive Medicaid and CHIP benefits in all states, as well as state… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/monthly-enrollment-test.clinical-quad-recall-dispersion-lag-enrollment-stall-v0.2
Clinical Quad Recall Dispersion Lag Enrollment Stall v0.2
What this is
A small dataset that tests one question:
Can you detect when enrollment is moving toward stall, not just under pressure?
This repo focuses on trial operations.
It models a system where:
batch recall disrupts flow
site dispersion weakens coordination
replacement lag delays recovery
active patient count falls under pressure
Run this first
Generate baseline predictions:
python… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-recall-dispersion-lag-enrollment-stall-v0.2.separate-chip-enrollment-by-month-and-state-histor
Separate CHIP Enrollment by Month and State – Historic CAA/Unwinding Period
Description
This historic dataset with total enrollment in separate CHIP programs by month and state was created to fulfill reporting requirements under section 1902(tt)(1) of the Social Security Act, which was added by section 5131(b) of subtitle D of title V of division FF of the Consolidated Appropriations Act, 2023 (P.L. 117-328) (CAA, 2023). For each month from April 1, 2023, through June 30… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/separate-chip-enrollment-by-month-and-state-histor.clinical-quad-batch-recall-site-dispersion-replacement-lag-active-patients-enrollment-stall-v0.1What this repo does
This dataset models trial disruption risk from batch recall propagation. It predicts when the interaction between a batch recall event, site dispersion, replacement lag, and active patient volume produces an enrollment stall and operational pause.
Core quad
batch_recall_flag
site_dispersion_index
replacement_lag_days
active_patient_count
Prediction target
label_enrollment_stall
Row structure
Each row represents a trial supply shock snapshot after a recall signal. The model… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-batch-recall-site-dispersion-replacement-lag-active-patients-enrollment-stall-v0.1.