OGLE-2017-BLG-1434Lb: Eighth q < 1 * 10^-4 Mass-Ratio Microlens Planet Confirms Turnover in Planet Mass-Ratio Function
Bibliographic record
Abstract
We report the discovery of a cold Super-Earth planet (m_p=4.4 +/- 0.5 M_Earth) orbiting a low-mass (M=0.23 +/- 0.03 M_Sun) M dwarf at projected separation a_perp = 1.18 +/- 0.10 AU, i.e., about 1.9 times the snow line. The system is quite nearby for a microlensing planet, D_Lens = 0.86 +/- 0.09 kpc. Indeed, it was the large lens-source relative parallax pi_rel=1.0 mas (combined with the low mass M) that gave rise to the large, and thus well-measured, "microlens parallax" that enabled these precise measurements. OGLE-2017-BLG-1434Lb is the eighth microlensing planet with planet-host mass ratio q < 1 * 10^-4. We apply a new planet-detection sensitivity method, which is a variant of "V/V_max", to seven of these eight planets to derive the mass-ratio function in this regime. We find dN/d(ln q) ~ q^p, with p = 1.05 (+0.78,-0.68), which confirms the "turnover" in the mass function found by Suzuki et al. relative to the power law of opposite sign n = -0.93 +/- 0.13 at higher mass ratios q >~ 2 * 10^-4. We combine our result with that of Suzuki et al. to obtain p = 0.73 (+0.42,-0.34).
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".