EFFECTS OF STRONG GRAVITATIONAL LENSING ON MILLIMETER-WAVE GALAXY NUMBER COUNTS
Bibliographic record
Abstract
We study the effects of strong lensing on the observed number counts of millimeter sources using a ray-tracing simulation and two number count models of unlensed sources. We employ a quantitative treatment of maximum attainable magnification factor depending on the physical size of the sources, also accounting for effects of lens halo ellipticity. We calculate predicted number counts and redshift distributions of millimeter galaxies including the effects of strong lensing and compare with the recent source count measurements of the South Pole Telescope (SPT). The predictions have large uncertainties, especially the details of the mass distribution in lens galaxies and the finite extent of sources, but the SPT observations are in good agreement with predictions. The sources detected by SPT are predicted to largely consist of strongly lensed galaxies at z > 2. The typical magnifications of these sources strongly depend on both the assumed unlensed source counts and the flux of the observed sources.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".