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
We have used the first ∼3 years of 3.4 μm (W1) and 4.6 μm (W2) observations from the WISE and NEOWISE missions to create a full-sky set of time-resolved coadds. As a result of the WISE survey strategy, a typical sky location is visited every six months and is observed during 12 exposures per visit, with these exposures spanning a ∼1 day time interval. We have stacked the exposures within such ∼1 day intervals to produce one coadd per band per visit - that is, one coadd every six months at a given position on the sky in each of W1 and W2. For most parts of the sky, we have generated six epochal coadds per band, with one visit during the fully cryogenic WISE mission, one visit during NEOWISE, and then, after a 33-month gap, four more visits during the NEOWISE-Reactivation mission phase. These coadds are suitable for studying long-timescale mid-infrared variability and measuring motions to ∼1.3 mag fainter than the single-exposure detection limit. In most sky regions, our coadds span a 5.5-year time period and therefore provide a >10× enhancement in time baseline relative to that available for the AllWISE catalog's apparent motion measurements. As such, the signature application of these new coadds is expected to be motion-based identification of relatively faint brown dwarfs, especially those cold enough to remain undetected by Gaia.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.027 |
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