197 CANDIDATES AND 104 VALIDATED PLANETS IN K2 's FIRST FIVE FIELDS
Bibliographic record
Abstract
We present 197 planet candidates discovered using data from the first year of the NASA K2 mission (Campaigns 0-4), along with the results of an intensive program of photometric analyses, stellar spectroscopy, high-resolution imaging, and statistical validation. We distill these candidates into sets of 104 validated planets (57 in multi-planet systems), 30 false positives, and 63 remaining candidates. Our validated systems span a range of properties, with median values of R P = 2.3 {R}\oplus , P = 8.6 days, {T}{eff} = 5300 K, and Kp = 12.7 mag. Stellar spectroscopy provides precise stellar and planetary parameters for most of these systems. We show that K2 has increased by 30% the number of small planets known to orbit moderately bright stars (1-4 R ⊕, Kp = 9-13 mag). Of particular interest are 76 planets smaller than 2 R ⊕, 15 orbiting stars brighter than Kp = 11.5 mag, 5 receiving Earth-like irradiation levels, and several multi-planet systems—including 4 planets orbiting the M dwarf K2-72 near mean-motion resonances. By quantifying the likelihood that each candidate is a planet we demonstrate that our candidate sample has an overall false positive rate of 15%-30%, with rates substantially lower for small candidates (\lt 2{R}\oplus ) and larger for candidates with radii \gt 8{R}\oplus and/or with P\lt 3 {{days}}. Extrapolation of the current planetary yield suggests that K2 will discover between 500 and 1000 planets in its planned four-year mission, assuming sufficient follow-up resources are available. Efficient observing and analysis, together with an organized and coherent follow-up strategy, are essential for maximizing the efficacy of planet-validation efforts for K2, TESS, and future large-scale surveys.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".