OPTICALLY SELECTED BL LACERTAE CANDIDATES FROM THE SLOAN DIGITAL SKY SURVEY DATA RELEASE SEVEN
Bibliographic record
Abstract
We present a sample of 723 optically selected BL Lac candidates from the Sloan Digital Sky Survey Data Release 7 (SDSS DR7) spectroscopic database encompassing 8250 deg(2) of sky; our sample constitutes one of the largest uniform BL Lac samples yet derived. Each BL Lac candidate has a high-quality SDSS spectrum from which we determine spectroscopic redshifts for similar to 60% of the objects. Redshift lower limits are estimated for the remaining objects utilizing the lack of host galaxy flux contamination in their optical spectra; we find that objects lacking spectroscopic redshifts are likely at systematically higher redshifts. Approximately 80% of our BL Lac candidates match to a radio source in FIRST/NVSS, and similar to 40% match to a ROSAT X-ray source. The homogeneous multi-wavelength coverage allows subdivision of the sample into 637 radio-loud BL Lac candidates and 86 weak-featured radio-quiet objects. The radio-loud objects broadly support the standard paradigm unifying BL Lac objects with beamed radio galaxies. We propose that the majority of the radio-quiet objects may be lower-redshift (z < 2.2) analogs to high-redshift weak line quasars (i.e., active galactic nucleus with unusually anemic broad emission line regions). These would constitute the largest sample of such objects, being of similar size and complementary in redshift to the samples of high-redshift weak line quasars previously discovered by the SDSS. However, some fraction of the weak-featured radio-quiet objects may instead populate a rare and extreme radio-weak tail of the much larger radio-loud BL Lac population. Serendipitous discoveries of unusual white dwarfs, high-redshift weak line quasars, and broad absorption line quasars with extreme continuum dropoffs blueward of rest-frame 2800 angstrom are also briefly described.
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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 | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".