HerMES: SPIRE Science Demonstration Phase maps★†‡
Bibliographic record
Abstract
We describe the production and verification of sky maps of the five Spectral and Photometric Imaging Receiver (SPIRE) fields observed as part of the Herschel Multi-tiered Extragalactic Survey (HerMES) during the Science Demonstration Phase (SDP) of the Herschel mission. We have implemented an iterative map-making algorithm [The SPIRE-HerMES Iterative Mapper (SHIM)] to produce high fidelity maps that preserve extended diffuse emission on the sky while exploiting the repeated observations of the same region of the sky with many detectors in multiple scan directions to minimize residual instrument noise. We specify here the SHIM algorithm and outline the various tests that were performed to determine and characterize the quality of the maps and verify that the astrometry, point source flux and power on all relevant angular scales meet the needs of the HerMES science goals. These include multiple jackknife tests, determination of the map transfer function and detailed examination of the power spectra of both sky and jackknife maps. The map transfer function is approximately unity on scales from 1 arcmin to 1°. Final maps (v1.0), including multiple jackknives, as well as the SHIM pipeline, have been used by the HerMES team for the production of SDP papers.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.023 |
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".