CHARACTERIZING LENSES AND LENSED STARS OF HIGH-MAGNIFICATION SINGLE-LENS GRAVITATIONAL MICROLENSING EVENTS WITH LENSES PASSING OVER SOURCE STARS
Bibliographic record
Abstract
We present the analysis of the light curves of nine high-magnification single-lens gravitational microlensing events with lenses passing over source stars, including OGLE-2004-BLG-254, MOA-2007-BLG-176, MOA-2007-BLG-233/OGLE-2007-BLG-302, MOA-2009-BLG-174, MOA-2010-BLG-436, MOA-2011-BLG-093, MOA-2011-BLG-274, OGLE-2011-BLG-0990/MOA-2011-BLG-300, and OGLE-2011-BLG-1101/MOA-2011-BLG-325. For all of the events, we measure the linear limb-darkening coefficients of the surface brightness profile of source stars by measuring the deviation of the light curves near the peak affected by the finite-source effect. For seven events, we measure the Einstein radii and the lens-source relative proper motions. Among them, five events are found to have Einstein radii of less than 0.2 mas, making the lenses very low mass star or brown dwarf candidates. For MOA-2011-BLG-274, especially, the small Einstein radius of θ E ∼ 0.08 mas combined with the short timescale of t E ∼ 2.7 days suggests the possibility that the lens is a free-floating planet. For MOA-2009-BLG-174, we measure the lens parallax and thus uniquely determine the physical parameters of the lens. We also find that the measured lens mass of ∼0.84 M ☉ is consistent with that of a star blended with the source, suggesting that the blend is likely to be the lens. Although we did not find planetary signals for any of the events, we provide exclusion diagrams showing the confidence levels excluding the existence of a planet as a function of the separation and mass ratio.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".