Archival Legacy Investigations of Circumstellar Environments: Overview and First Results
Bibliographic record
Abstract
We are currently conducting a comprehensive and consistent re-processing of archival HST-NICMOS corona-graphic surveys using advanced PSF subtraction methods, entitled the Archival Legacy Investigations of Cir-cumstellar Environments program (ALICE, HST/AR 12652). This virtual campaign of about 400 targets has already produced numerous new detections of previously unidentified point sources and circumstellar structures. We present five newly spatially resolved debris disks revealed in scattered light by our analysis of the archival data. These images provide new views of material around young solar-type stars at ages corresponding to the period of terrestrial planet formation in our solar system. We have also detected several new candidate substellar companions, for which there are ongoing followup campaigns (HST/WFC3 and VLT/SINFONI in ADI mode). Since the methods developed as part of ALICE are directly applicable to future missions (JWST, AFTA corona-graph) we emphasize the importance of devising optimal PSF subtraction methods for upcoming coronagraphic imaging missions. We describe efforts in defining direct imaging high-level science products (HLSP) standards that can be applicable to other coronagraphic campaigns, including ground-based (e.g., Gemini Planet Imager), and future space instruments (e.g., JWST). ALICE will deliver a first release of HLSPs to the community through
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".