Performance of the integral field spectrograph for the Gemini Planet Imager
Bibliographic record
Abstract
We present performance results, from in-lab testing, of the Integral Field Spectrograph (IFS) for the Gemini Planet Imager (GPI). GPI is a facility class instrument for the Gemini Observatory with the primary goal of directly detecting young Jovian planets. The GPI IFS is based on concepts from the OSIRIS instrument at Keck and utilizes an infrared transmissive lenslet array to sample a rectangular 2.8 x 2.8 arcsecond field of view. The IFS provides low-resolution spectra across five bands between 1 and 2.5μm. Alternatively, the dispersing element can be replaced with a Wollaston prism to provide broadband polarimetry across the same five filter bands. The IFS construction was based at the University of California, Los Angeles in collaboration with the Université de Montr eal, Immervision and Lawrence Livermore National Laboratory. During its construction, we encountered an unusual noise source from microphonic pickup by the Hawaii-2RG detector. We describe this noise and how we eliminated it through vibration isolation. The IFS has passed its preship review and was shipped to University of California, Santa Cruz at the end of 2011 for integration with the remaining sub-systems of GPI. The IFS has been integrated with the rest of GPI and is delivering high quality spectral datacubes of GPI's coronagraphic field.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".