Erratum: “Giant Outer Transiting Exoplanet Mass (GOT ‘EM) Survey. II. Discovery of a Failed Hot Jupiter on a 2.7 yr, Highly Eccentric Orbit” (2021, AJ, 162, 154)
Bibliographic record
Abstract
In the original analysis by Dalba et al. (2021) to confirm and characterize the Kepler-1704 system, an erroneous offset of 0.53878357713256 day was accidentally subtracted from the time stamps of the photometric measurements of this star acquired by the Kepler spacecraft. This photometry was then used in the comprehensive system modeling that yielded the final ephemeris of this exoplanet. As a result, parameters describing the timing of this planet’s orbit, most notably its conjunction (transit) time, were erroneously offset. This erratum serves to correct this error and the ephemeris of Kepler-1704 b. We added the 0.53878357713256 day offset to the time stamps of the Kepler photometry that was used in the original analysis. The corresponding flux values were unchanged. Besides the time stamps, we did not alter any other data product. We then conducted the joint modeling of the stellar and planetary parameters of the Kepler-1704 system using EXOFASTv2 (Eastman et al. 2019) exactly as described in Section 3 of Dalba et al. (2021). All priors and EXOFASTv2 settings were left as described in the original analysis. This new fit converged following the same criteria applied in the original analysis. We again observed a bimodality in mass and age of Kepler-1704 as described in Section 3.1 of Dalba et al. (2021). We selected the lower stellar mass solution just as before and calculated the updated stellar and planetary parameters, which are listed in Tables 1 and 2, respectively. The only parameter values in Tables 1 and 2 that changed significantly between Dalba et al. (2021) and this analysis are conjunction time (TC), periastron time (TP), and eclipse time (TS). This is expected given that the only change to the inputs to the EXOFASTv2 fit were the time stamps of the Kepler photometry. Changes for other parameters other than those listed above were only due to rounding error or small statistical variations in the Markov chain Monte Carlo analysis, and were all well within the 1σ uncertainties. Figure 1 shows the Kepler light curves with the updated time stamps and the updated best-fit models. This figure is analogous to Figure 5 of Dalba et al. (2021). Table 3 shows the updated predictions for the timing of future transits and periastron passages. Asexpected, the time of these events are shifted forward by the value of the time stamp offset relative to the corresponding times published in Table 4 of Dalba et al. (2021). We conducted two consistency checks of the new ephemeris for Kepler-1704 b. First, we accessed the Kepler Pre-search Data Conditioning Simple Aperture Photometry (PDCSAP; Jenkins et al. 2010; Smith et al. 2012; Stumpe et al. 2012) photometry of Kepler-1704 from Quarters 2 and 13 via the Mikulski Archive for Space Telescopes but we did not conduct any additional detrending. We inserted the unaltered PDCSAP transit light curves into the exact same EXOFASTv2 fit, which proceeded until convergence. The resulting orbital elements are consistent this with those listed in Table 2. Second, we accessed the Transit and Ephemeris Service on the NASA Exoplanet Archive15 and predicted future transit times of Kepler-1704 b using the planet candidate solution from the Kepler Quarter 1–17 Data Release 25 Supplemental Kepler Object of Interest Table. The resulting transit times forthe four events spanning the years 2023–2031 agreed with the transit times listed in Table 3 to within 1 minute.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.031 |
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".