The SLoWPoKES catalog of low‐mass ultra–wide binaries: A cool stars resource for testing fundamental properties and for constraining binary formation theory
Bibliographic record
Abstract
Abstract We present results from the Sloan Low‐mass Wide Pairs of Kinematically Equivalent Stars (SLoWPoKES) catalog of ultra‐wide (103–105.5 AU), low‐mass (K5–M7) common proper motion binaries. We constructed a Galactic model, based on empirical stellar number density and 3D velocity distributions, to select bona fide pairs with probability of chance alignment <5 %, making SLoWPoKES an efficient sample for followup observations. Our initial catalog contains 1342 disk dwarf, subdwarf, and white dwarf‐red dwarf systems and is the largest collection of low‐mass, wide binaries ever assembled. The diversity – in mass, metallicity, age, and evolutionary states – of SLoWPoKES pairs makes it a valuable resource of coeval laboratories to examine and constrain the physical properties of low‐mass stars. SLoWPoKES pairs show signatures of two (or more) formation modes in the distribution of the physical separation and higher‐order multiplicity. Neither dynamical dissipation of primordial triples/quadruples or dynamical capture of ejected stars can explain the observed populations by itself. We use follow‐up spectroscopic observations to recalibrate the metallicity‐sensitive ζTiO/CaH index by assuming that both members of the binary system have the same composition. Our new formulation is a significantly better tracer of absolute metallicity, particularly for the early‐type M dwarfs. The catalogs are publicly available on a custom data visualization portal. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".