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 engineered a foundational data package in R, incorporating biological parameters, growth rates, and mortality Z-scores to support simulation-based decision-making. Using R Shiny and JavaScript, Nicholas built a model comparison app that enables side-by-side evaluation of Stock Synthesis runs with interactive metrics and recruitment plots. He also produced Quarto-based workshop materials and site content to accelerate training. By integrating legacy binaries and configuration management, he ensured versioning, rollback, and reproducibility for model-driven fisheries management.
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
83 people
Work 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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