datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Dist_Uncertainty
Dist_Uncertainty – Hyperspectral Case Studies for Plant Trait Uncertainty Assessment
Dataset Description
This dataset contains hyperspectral remote sensing imagery and associated land cover labels used as out-of-domain (OOD) test cases for evaluating uncertainty estimation methods in deep learning-based plant trait retrievals. It accompanies the paper by Cherif et al. (2025, Biogeosciences) and supports the evaluation of a distance-based uncertainty method (Dis_UN)… See the full description on the dataset page: https://huggingface.co/datasets/Avatarr05/Dist_Uncertainty.kin8nmOpenHermes-headlines-2017-2019-uncertainty
OpenHermes-headlines-2017-19-uncertainty
Dataset used to train a variant of the complex backdoored models in the paper Future Events as Backdoor Triggers: Investigating Temporal Vulnerabilities in LLMs. This dataset is an adapted version of a random subset of instances from the OpenHermes-2.5 Dataset.
These backdoored models are trained to demonstrate two types of behavior conditional on whether they recognize they are in training versus deployment. The training behavior… See the full description on the dataset page: https://huggingface.co/datasets/saraprice/OpenHermes-headlines-2017-2019-uncertainty.uncertainty-incompleteness-functional-unknowns-genomics-v01
Dataset
ClarusC64/uncertainty-incompleteness-functional-unknowns-genomics-v01
This dataset tests one capability.
Can a model resist inventing biological function when evidence is incomplete.
Core rule
Genomics contains large unknowns.
A claim must respect
incomplete annotation
context specific regulation
limits of prediction
absence of functional validation
Prediction is not proof.
Annotation is not mechanism.
Expression is not causation.
Canonical labels… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/uncertainty-incompleteness-functional-unknowns-genomics-v01.lag-lock-uncertainty-economics
lag-lock uncertainty Economics Dataset
Dataset Description
Summary
Synthetic 200-row dataset for lag-lock uncertainty measurement and computational experiments.
Supported Tasks
Economic analysis
Climate Economics research
Computational economics
Languages
English (metadata and documentation)
Python (code examples)
Dataset Structure
Data Fields
id: Unique observation id
year: Synthetic climate-policy year… See the full description on the dataset page: https://huggingface.co/datasets/EconomicTermDevelopments/lag-lock-uncertainty-economics.protein_structure_uncertainty_auditor_v01Protein Structure Uncertainty Auditor v0.1
This dataset tests whether language models can correctly recognize uncertainty and epistemic limits when talking about protein structure and AlphaFold style predictions.
Each row contains
claim
grounding_status
rationale_hint
correct_action
grounding_status values
groundedthe claim is a reasonable interpretation of structure and confidence
speculativethe claim is plausible but needs more context or experiment
unfoundedthe claim overreaches what… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/protein_structure_uncertainty_auditor_v01.protein_structure_uncertainty_auditor_v0.2Protein Structure Uncertainty Auditor
GoalDetect when predicted protein structures are too uncertain for downstream use.
Model must output
uncertainty_flag (yes/no)
uncertainty_type
recommendation
This dataset tests whether models can audit structural confidence before use in:
drug design
docking
mutation mapping
function inference
Run scorer
python scorer.py --predictions predictions.jsonl --test_csv data/test.csv
uncertainty_0.1uncertainty-projection-discipline-climate-v01
Dataset
ClarusC64/uncertainty-projection-discipline-climate-v01
This dataset tests one capability.
Can a model project forward without pretending certainty where none exists.
Core rule
Climate projections must respect uncertainty.
That means
naming uncertainty
using ranges not point certainties
treating scenarios as conditional
avoiding irreversible or guaranteed claims
Canonical labels
WITHIN_SCOPE
OUT_OF_SCOPE
Files… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/uncertainty-projection-discipline-climate-v01.OpenHermes-headlines-2020-2022-uncertaintyuncertainty-followup-discipline-radiology-v01Uncertainty and Follow Up Discipline v01
What this dataset is
This dataset evaluates whether a system acknowledges uncertainty and recommends appropriate follow up instead of prematurely closing a case.
You give the model:
Imaging findings
A report level statement
You ask one question.
When certainty is not possible
does the system act responsibly
Why this matters
Radiology often operates under uncertainty.
The danger is not uncertainty itself.
The danger is hiding it.
Common failure patterns:… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/uncertainty-followup-discipline-radiology-v01.uncertainty_0.05uncertainty_0.15