datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
autonomous-driving-decoherence-onset-detection-v0.1What this dataset tests
Whether a system can detect
the onset of system-wide decoherence.
Decoherence means:
camera, lidar, radar, and map
stop supporting a unified scene narrative.
Required outputs
decoherence_onset_timestamp
coherence_drop_delta
affected_modalities
narrative_conflict_flag
onset_confidence
early_warning_score
Scoring conventions
timestamp is seconds from window start
coherence drop delta is 0 to 1
conflict flag is 1 when the narratives diverge
early warning… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/autonomous-driving-decoherence-onset-detection-v0.1.2d-vdw-interface-decoherence-v0.1Goal
Predict failure in stacked 2D devices.
Core idea
Stacked device failure arrives when coupling collapses:
twist angle and alignmentinterlayer charge transferI-V behavior and leakagecontact resistance
stop moving together.
Inputs
twist angle
TEM alignment score
interlayer charge transfer efficiency
contact resistance
I-V nonlinearity index
leakage current
thermal cycles
humidity exposure
Required outputs
interface_coherence_score
decoherence_flag
decoherence_type… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/2d-vdw-interface-decoherence-v0.1.ai-constitutional-cross-axis-decoherence-mapping-v0.1
Goal
Detect cross-axis decoherence.
Meaning:
the model looks helpful
but violates honesty or harmlessness
or evades while staying “safe”
This catches failures that single-axis checks miss.
Inputs
constitution_excerptsuser_requestmodel_output
Required outputs
axis_status_mapFormat example: honesty=ok|harmlessness=violation|helpfulness=appears_ok
cross_axis_decoherence_flagyes | no
decoherence_patternExamples:
helpful_but_fabricated
unsafe_helpfulness… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ai-constitutional-cross-axis-decoherence-mapping-v0.1.aviation-pilot-vehicle-decoherence-source-attribution-v0.1What this dataset tests
Whether a system can correctly identifythe source of pilot–vehicle loop decoherence.
Sources may be:
pilotaircraftenvironmentmixednone
Key insightCorrect attribution determinesthe correct recovery action.
Required outputs
primary_decoherence_source
source_confidence
resonance_pattern_type
escalation_likelihood
contributing_factors
attribution_rationale
Use case
Layer two of Pilot–Vehicle Loop Coherence Under Stress.Feeds adaptive intervention and crew… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/aviation-pilot-vehicle-decoherence-source-attribution-v0.1.fusion-cross-field-decoherence-precursor-detection-v0.1What this dataset tests
Whether a system can detect early decoherenceacross three linked stability surfaces:
magnetic stability
temperature gradient structure
impurity behavior
The goal is not to detect quench.The goal is to detect the precursor window10 to 100 milliseconds before quench.
Required outputs
decoherence_precursor_flag
onset_ms_before_quench
precursor_pattern_label
disruption_risk_score
confidence_score
Use case
Layer 2 of COH-FUSION-001Plasma Stability Coherence… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/fusion-cross-field-decoherence-precursor-detection-v0.1.aviation-propulsion-aerodynamics-decoherence-precursor-detection-v0.1What this dataset tests
Whether a system can detect early decoherence
between propulsion behavior and aerodynamic response.
The signal is relationship drift:
lag expansion
correlation collapse
nonlinear divergence
oscillatory mismatch.
Required outputs
decoherence_onset_time
precursor_pattern_type
severity_gradient
failure_likelihood_index
estimated_time_to_critical_min
primary_decoupling_channels
Scoring conventions
onset time is minutes from window start
severity and… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/aviation-propulsion-aerodynamics-decoherence-precursor-detection-v0.1.alphafold-interface-decoherence-under-stress-detection-v0.1
What this dataset tests
Whether a model can detectstress-induced interface decoherencebefore full dissociation.
Stress modes covered
pH shiftheat stressoxidative stress
The failure mode
Contact maps stop predicting bindingand cross-interface signal transmission weakens.
Inputs
stress_typestress_level
baseline_interface_coherencebaseline_kd_nMbaseline_contact_stabilitybaseline_allosteric_cross_interface_score… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/alphafold-interface-decoherence-under-stress-detection-v0.1.