Planck 2013 results. XII. Diffuse component separation
Bibliographic record
Abstract
The development of Planck has been supported by:\n\t\t\t\t ESA; CNES and CNRS/INSU-IN2P3-INP (France); ASI, CNR, and INAF\n\t\t\t\t (Italy); NASA and DoE (USA); STFC and UKSA (UK); CSIC, MICINN,\n\t\t\t\t JA and RES (Spain); Tekes, AoF and CSC (Finland); DLR and MPG\n\t\t\t\t (Germany); CSA (Canada); DTU Space (Denmark); SER/SSO (Switzerland);\n\t\t\t\t RCN (Norway); SFI (Ireland); FCT/MCTES (Portugal); PRACE (EU). A\n\t\t\t\t description of the Planck Collaboration and a list of its members, including the technical or scientific activities in which they have been\n\t\t\t\t involved, can be found at http://www.sciops.esa.int/index.php?\n\t\t\t\t project=planck&page=Planck_Collaboration. The authors acknowledge\n\t\t\t\t the support provided by the Advanced Computing and e-Science team at IFCA.\n\t\t\t\t This work made use of the COSMOS supercomputer, part of the STFC DiRAC\n\t\t\t\t HPC Facility. Some of the results in this paper have been derived using the\n\t\t\t\t HEALPix package.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".