Pith. sign in

Citation notice #5057 · 2026-07-11 03:19:08.722131+00:00

Detection of CO, H$_2$O, and OH in WASP-18b with JWST/NIRISS using Direct-Extracted Spectra and Cross-Correlation

Correction Crossref Open

cites SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python, which carries a correction notice dated 2020-03-04. One-hop deterministic notice: the citation edge exists in the Pith bibliography graph; no model judged whether the citation was load-bearing.

This is not a judgment on the citing paper.

Citing paper Event page Original DOI Notice DOI File a formal challenge All reference changes

01Evidence

Raw extraction · bibliography line · bibliography index 51

Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Medicine, 17, 261, doi: 10.1038/s41592-019-0686-2 19 12 10 8 6 4 2 log10 VMR (H2O) 6 5 4 3 2 1 0 1 2 equ chem 12 10 8 6 4 2 log10 VMR (CO) 6 5 4 3 2 1 0 1 2 12 10 8 6 4 2 log10 VMR (CO2) 6 5 4 3 2 1 0 1 2 12 10 8 6 4 2 log10 VMR (HCN) 6 5 4 3 2 1 0 1 2 log10 Pressure (bar) 12 10 8 6 4 2 log10 VMR (H ) 6 5 4 3 2 1 0 1 2 12 10 8 6 4 2 log10 VMR (OH) 6 5 4 3 2 1 0 1 2 12 10 8 6 4 2 log10 VMR (FeH) 6 5 4 3 2 1 0 1 2 12 10 8 6 4 2 log10 VMR (TiO) 6 5 4 3 2 1 0 1 2 12 10 8 6 4 2 log10 VMR (VO) 6 5 4 3 2 1 0 1 2 free+diss. free+diss. Coulombe et al. 2023 Figure 12.Posterior distributions of the VMRs for key atmospheric species in WASP-18b. The blue lines and shaded regions represent the median VMR profiles and their 1σuncertainties derived from our equilibrium chemistry retrieval. The red histograms show the posterior distributions of the deep abundances retrieved from our free chemistry with thermal dissociation (free+diss.) retrieval. For comparison, the yellow-filled histograms display the corresponding results from the free+diss. retrieval of L.-P. Coulombe et al. (2023)

02Event

Type
Correction
Source
Crossref
Original DOI
10.1038/s41592-019-0686-2
Notice DOI
10.1038/s41592-020-0772-5
Date
2020-03-04
Title
Author Correction: SciPy 1.0: fundamental algorithms for scientific computing in Python
Reasons
['Correction']
Work
SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python (2020) Nature Methods

Schema constants (for re-runners): correction · crossref

03Dispute this notice

If this citation does not depend on the flagged claim, or the event is wrong, say so. Disputes are public. For a signed challenge against the paper itself, use the formal challenge form.