Planck 2015 resultsXV. Gravitational lensing
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
Acknowledgements. The Planck Collaboration acknowledges the support of: \nESA; CNES and CNRS/INSU-IN2P3-INP (France); ASI, CNR, and INAF \n(Italy); NASA and DoE (USA); STFC and UKSA (UK); CSIC, MINECO, \nJA, and RES (Spain); Tekes, AoF, and CSC (Finland); DLR and MPG \n(Germany); CSA (Canada); DTU Space (Denmark); SER/SSO (Switzerland); \nRCN (Norway); SFI (Ireland); FCT/MCTES (Portugal); ERC and PRACE \n(EU). A description of the Planck Collaboration and a list of its members, indicating which technical or scientific activities they have been involved in, can be found at http://www.cosmos.esa.int/web/planck/ \nplanck-collaboration. Some of the results in this paper have been derived \nusing the HEALPix package. We acknowledge support from the Science and \nTechnology Facilities Council [grant number ST/L000652/1]. The research leading to these results has received funding from the European Research Council \nunder the European Union’s Seventh Framework Programme (FP/2007-2013)/ \nERC Grant Agreement No. [616170]. Part of this work was undertaken on the \nSTFC DiRAC HPC Facilities at the University of Cambridge funded by UK BIS \nNational E-infrastructure capital grants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it