MOshima-PIFSC/ISC_OSworkflow_training
Jan 2025 – Jan 2025
1 Month active
Languages Used
BibTeXCSSHTMLJavaScriptLaTeXMarkdownQuartoR
Technical Skills
Academic Writing SupportCSSCitation ManagementCode CleanupCode ReviewConfiguration Management
N-DucharmeBarth-NOAA
PROFILE
N-ducharmebarth-noaa
Nicholas Ducharme-Barth developed core training and modeling infrastructure for the MOshima-PIFSC/ISC_OSworkflow_training repository, focusing on fisheries ecological modeling and reproducible workflows. He created a foundational data package in R with biological parameters, growth rates, and mortality Z-scores to support simulation-based decision-making. Using R Shiny and JavaScript, Nicholas built a model comparison dashboard enabling side-by-side evaluation of Stock Synthesis runs with interactive metrics and recruitment plots. He also produced Quarto-based workshop materials, templates, and site content to streamline training and documentation. By integrating legacy binaries and configuration management, he enhanced version control and reproducibility for fisheries management applications.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
18Total
Bugs
0
Commits
18
Features
4
Lines of code
244,436
Activity Months1
Your Network
88 peopleWork History
January 2025
18 Commits • 4 Features
Jan 1, 2025January 2025: Delivered core training and modeling infrastructure for ISC_OSworkflow_training. Implemented a foundational fisheries ecological modeling data package with biological parameters, growth rates, and mortality Z-scores to support decision-making in simulations; launched a Stock Synthesis model comparison Shiny app enabling side-by-side evaluation of model runs with UI for introduction, metrics, and recruitment plots; produced Day 1–4 Quarto-based workshop materials, templates, slides, assets, and site content to accelerate training and documentation; added Stock Synthesis legacy binaries to support versioning and rollback. The work enhances training readiness, reproducibility, and model-driven fisheries management insights.
18 Commits • 4 Features
Jan 1, 2025January 2025: Delivered core training and modeling infrastructure for ISC_OSworkflow_training. Implemented a foundational fisheries ecological modeling data package with biological parameters, growth rates, and mortality Z-scores to support decision-making in simulations; launched a Stock Synthesis model comparison Shiny app enabling side-by-side evaluation of model runs with UI for introduction, metrics, and recruitment plots; produced Day 1–4 Quarto-based workshop materials, templates, slides, assets, and site content to accelerate training and documentation; added Stock Synthesis legacy binaries to support versioning and rollback. The work enhances training readiness, reproducibility, and model-driven fisheries management insights.
January 2025
Activity
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Quality Metrics
Correctness93.4%
Maintainability92.2%
Architecture92.2%
Performance92.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
BibTeXCSSHTMLJavaScriptLaTeXMarkdownQuartoRXMLYAML
Technical Skills
Academic Writing SupportCSSCitation ManagementCode CleanupCode ReviewConfiguration ManagementContent CreationDashboard DevelopmentData AnalysisData EngineeringData VisualizationDependency ManagementDocumentationDocumentation ManagementEcological Modeling
Repositories Contributed To
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