Bibliographic record
Abstract
Among active galactic nuclei, BL Lac objects show extreme properties that have been interpreted as the effect of relativistic beaming on the emission from a plasma jet oriented close to the line of sight. The Doppler amplification of the jet emission makes them ideal targets for studying jet physics. In particular, low-power BL Lacs (LPBL) are very interesting because they probe the jet formation and emission processes at the lowest levels of accretion. However, they are difficult to identify since their emission is swamped by the radiation from the host galaxy in most observing bands. In this paper we propose a new LPBL selection method based on the mid-infrared emission, in addition to the traditional optical indices. We considered the radio-selected sample of Best & Heckman (2012, MNRAS, 421, 1569) and cross-matched it with the WISE all-sky survey. In a new diagnostic plane including the W2−W3 color and the Dn(4000) index, LPBL are located in a region scarcely populated by other sources. By filtering objects with small emission line equivalent width, we isolated 36 LPBL candidates up to redshift 0.15. Their radio luminosity at 1.4 GHz spans the range log Lr = 39.2−41.5 [erg s-1]. Considering the completeness of our sample, we analyzed the BL Lac luminosity function (RLF), finding a dramatic paucity of LPBL with respect to the extrapolation of the RLF toward low power. This requires a break in the RLF located at log Lr ~ 40.6 [erg s-1]. The consequent peak in the BL Lacs number density is possibly the manifestation of a minimum power required to launch a relativistic jet.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".