AITE Test Results#
Quantum Dot Control#
Quantum Dot Control Test v1.0
Charge stability diagrams are two-dimensional measurements that show how the electrical response of a quantum dot changes as voltages applied to control electrodes are varied. Given an image patch of a charge stability diagram, the model must output a three-state probability vector that the image patch displays a double-dot, a single-dot or no dot. The primary metric is mean squared error between output and expert-labeled state vectors.
Model ID |
Date Submitted |
Test Set |
Mean Squared Error (95% CI) |
|---|---|---|---|
Example Model 1 |
May 1, 2026 |
QDC Patches v1.0 |
0.27 (0.24, 0.30) |
Human Genome Variant Curation#
Human Genome Variant Curation Test v1.0
Given an image of a small region of the genome and text describing a set of variants in this region, the model must determine whether all of the given variants were correctly called. The primary metric is an unweighted linear combination of Type I and Type II error rates.
Model ID |
Date Submitted |
Test Set |
Average Error Rate (95% CI) |
|---|---|---|---|
Example Model 1 |
May 1, 2026 |
Genome Variant Visualization v1.0 |
0.5606 (0.5492, 0.5721) |
Public Safety Visual Event Recognition#
Public Safety Visual Event Recognition Test v1.0
Given a set of three video key frames, the model must output a yes or no decision whether the key frames provide evidence of a public safety event occurring. The primary metric is a detection cost function, which is a weighted linear combination of Type I and Type II error rates.
Model ID |
Date Submitted |
Test Set |
Detection Cost Function Value (95% CI) |
|---|---|---|---|
Example Model 1 |
May 1, 2026 |
Gumby v1.0 |
0.0688 (0.0309, 0.104) |