Literatura académica sobre el tema "Code source (informatique) – Documentation"

Abstract The recent UNCOVER survey with the James Webb Space Telescope (JWST) exploits the nearby cluster A2744 to create the deepest view of our Universe to date by leveraging strong gravitational lensing. In this work, we perform photometric fitting of more than 50,000 robustly detected sources out to z ∼ 15. We show the redshift evolution of stellar ages, star formation rates, and rest-frame colors across the full range of 0.2 ≲ z ≲ 15. The galaxy properties are inferred using the Prospector Bayesian inference framework using informative Prospector-β priors on the masses and star formation histories to produce joint redshift and stellar populations posteriors. Additionally, lensing magnification is performed on the fly to ensure consistency with the scale-dependent priors. We show that this approach produces excellent photometric redshifts with σ NMAD ∼ 0.03, of a similar quality to the established photometric redshift code EAzY. In line with the open-source scientific objective of this Treasury survey, we publicly release the stellar population catalog with this paper, derived from our photometric catalog adapting aperture sizes based on source profiles. This release (the catalog and all related documentation are accessible via the UNCOVER survey web page: https://jwst-uncover.github.io/DR2.html#SPSCatalogs with a copy deposited to Zenodo at doi:10.5281/zenodo.8401181) includes posterior moments, maximum likelihood spectra, star formation histories, and full posterior distributions, offering a rich data set to explore the processes governing galaxy formation and evolution over a parameter space now accessible by JWST.

Abstract Motivation RNA expression at isoform level is biologically more informative than at gene level and can potentially reveal cellular subsets and corresponding biomarkers that are not visible at gene level. However, due to the strong 3ʹ bias sequencing protocol, mRNA quantification for high-throughput single-cell RNA sequencing such as Chromium Single Cell 3ʹ 10× Genomics is currently performed at the gene level. Results We have developed an isoform-level quantification method for high-throughput single-cell RNA sequencing by exploiting the concepts of transcription clusters and isoform paralogs. The method, called Scasa, compares well in simulations against competing approaches including Alevin, Cellranger, Kallisto, Salmon, Terminus and STARsolo at both isoform- and gene-level expression. The reanalysis of a CITE-Seq dataset with isoform-based Scasa reveals a subgroup of CD14 monocytes missed by gene-based methods. Availability and implementation Implementation of Scasa including source code, documentation, tutorials and test data supporting this study is available at Github: https://github.com/eudoraleer/scasa and Zenodo: https://doi.org/10.5281/zenodo.5712503. Supplementary information Supplementary data are available at Bioinformatics online.

This paper is essentially a progress report on - the European Community terminology data bank, known as Eurodicautom, - the machine translation projects Systran and Eurotra - access to Community, European and American data banks. Eurodicom is now a fully developed electronic dictionary, containing about 334.000 terminological units (single words, phrases and abbreviations) in English, 318.000 in French, 239.000 in German, 150.000 in Italian, 145.000 in Danish, 136.000 in Dutch, 64.000 in Spanish, 10.000 in Portuguese and 700 in Latin (5 November 1984). Translations are accompanied by descriptieve, linguistic and documentary information (viz. definition, context, source, originating office, author, subject code and reliability rating). Eurodicautom is also available to the public on-line (for details apply to Echo, Customer Service, 15 avenue de La Faïencerie, L-1510 Luxemburg, tel. 352-20764). At present Systran provides machine translations for the Language pairs English-French, French-English and English-Italian. English-German is being introduced and French-German will become available shortly. Consideration is being given to developing systems from either French or English into Greek, Danish or Dutch. (Report Ian M. Pigott, 29 May 1984). Rapid post-editing (emphasis on accuracy or full post-editing (thorough revision) is always required. Work on Eurotra, a machine translation system of advanced design, is now well under way (Preparatory phase, 2 years, is all but terminated). Unlike Systran (language pairs, one way) Eurotra will be set up to supply translations from any source language available in the system into a number of target languages. The first results are due by 1989, after a phase of basic and applied linguistic research (2 years) and a phase of stabilization of the linguistic models and evaluation of results (18 months). There is a brief outline of the objectives and the programme of work in Council Decision 82/752/EEC, Official Journal of the European Communities, 1982 No L 317, pp. 19-23. Translators can now be assisted by Information Officers to consult titles, abstracts and full articles in some 140 Community, European and American data systems.

Besides source code, the fundamental source of information about open source software lies in documentation, and other non source code files, like README, INSTALL, or How-To files, commonly available in the software ecosystem. These documents, written in natural language, provide valuable information during the software development stage, but also in future maintenance and evolution tasks. DMOSS3 is a toolkit designed to systematically assess the quality of non source code content found in software packages. The toolkit handles a package as an attribute tree, and performs several tree traverse algorithms through a set of plugins, specialized in retrieving specific metrics from text, gathering information about the software. These metrics are later used to infer knowledge about the software, and composed together to build reports that assess the quality of specific features. This paper discusses the motivations for this work, continues with a description of the toolkit implementation and design goals. This is followed by an example of its usage to process a software package, and the produced report.

Computational notebooks allow data scientists to express their ideas through a combination of code and documentation. However, data scientists often pay attention only to the code, and neglect creating or updating their documentation during quick iterations. Inspired by human documentation practices learned from 80 highly-voted Kaggle notebooks, we design and implement Themisto, an automated documentation generation system to explore how human-centered AI systems can support human data scientists in the machine learning code documentation scenario. Themisto facilitates the creation of documentation via three approaches: a deep-learning-based approach to generate documentation for source code, a query-based approach to retrieve online API documentation for source code, and a user prompt approach to nudge users to write documentation. We evaluated Themisto in a within-subjects experiment with 24 data science practitioners, and found that automated documentation generation techniques reduced the time for writing documentation, reminded participants to document code they would have ignored, and improved participants’ satisfaction with their computational notebook.