A New Standard for Assessing the Performance of High Contrast Imaging Systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract As planning for the next generation of high contrast imaging instruments (e.g., WFIRST, HabEx, and LUVOIR, TMT-PFI, EELT-EPICS) matures and second-generation ground-based extreme adaptive optics facilities (e.g., VLT-SPHERE, Gemini-GPI) finish their principal surveys, it is imperative that the performance of different designs, post-processing algorithms, observing strategies, and survey results be compared in a consistent, statistically robust framework. In this paper, we argue that the current industry standard for such comparisons—the contrast curve—falls short of this mandate. We propose a new figure of merit, the “performance map,” that incorporates three fundamental concepts in signal detection theory: the true positive fraction, the false positive fraction, and the detection threshold. By supplying a theoretical basis and recipe for generating the performance map, we hope to encourage the widespread adoption of this new metric across subfields in exoplanet imaging.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it