Quasars in the 2MASS Second Incremental Data Release
Bibliographic record
Abstract
Using the 2MASS Second Incremental Data Release, we have searched for near-infrared counterparts to 13214 quasars from the Veron-Cetty & Veron catalog. We have detected counterparts within 4'' for 2277 of the approximately 6320 quasars within the area covered by the 2MASS Second Incremental Data Release. Only 1.6% of these are expected to be chance coincidences. Though this sample is heterogeneous, we find that known radio-loud quasars are more likely to have large near-infrared-to-optical luminosity ratios than radio-quiet quasars are, at a statistically significant level. This is consistent with dust-reddened quasars being more common in radio-selected samples than in optically selected samples, due to stronger selection effects against dust-reddened quasars in the latter. We also find a statistically significant dearth of optically luminous quasars with large near-infrared-to-optical luminosity ratios. This can be explained in a dust obscuration model but not in a model where synchrotron emission extends from the radio into the near-infrared and creates such large ratios. We also find that selection of quasar candidates from the B - J / J - K color-color diagram, modeled on the V - J / J - K selection method of Warren, Hewett, & Foltz, is likely to be more sensitive to dust-obscured quasars than selection using only infrared-infrared colors.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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".