Variability-selected Quasars in MACHO Project Magellanic Cloud Fields
Bibliographic record
Abstract
We present 47 spectroscopically-confirmed quasars discovered behind the Magellanic Clouds identified via photometric variability in the MACHO database. Thirty-eight quasars lie behind the Large Magellanic Cloud and nine behind the Small Magellanic Cloud, more than tripling the number of quasars previously known in this region. The quasars cover the redshift interval 0.2 < z < 2.8 and apparent mean magnitudes 16.6 < V < 20.1. We discuss the details of quasar candidate selection based on time variability in the MACHO database and present results of spectroscopic follow-up observations. Our follow-up detection efficiency was 20%; the primary contaminants were emission-line Be stars in Magellanic Clouds. For the 47 quasars discovered behind the Magellanic Clouds plus an additional 12 objects previously identified in this region, we present 7.5-year MACHO V- and R-band lightcurves with average sampling times of 2-10 days.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".