
Worked on the mcgoodman/widow-assessment-update repository to enhance the widowfish stock assessment model, focusing on improving reliability and decision support for fisheries science. Developed and refined model features in R and C++, including updates to data loading for age and length composition, selectivity parameter adjustments, and the addition of depletion outputs for robust sensitivity analysis. Introduced comprehensive sensitivity analysis tooling for Stock Synthesis (SS3) models, enabling efficient scenario testing and comparative reporting. Modernized the codebase by cleaning up outdated scripts and improving data weighting methods, resulting in increased model accuracy, reproducibility, and efficiency for stock assessment workflows.
May 2025 monthly summary for mcgoodman/widow-assessment-update: Delivered two core features that advance model fidelity and enable robust sensitivity testing for SS3 models. Implemented widow assessment model data weighting enhancements to reflect data source influence by updating weighting parameters in starter.ss and 2025widow.ctl (commit 61c06a47a210a146905b12da3991016912b9139d). Introduced comprehensive sensitivity analysis tooling for SS3 models, including environment setup, base and scenario runs, and generation of comparative plots and tables; consolidated cleanup by removing outdated sensitivity analysis scripts (commits AllSensitivityScript added; AllSensitivityAnalysisScript; and related cleanup). Fixed a critical bug by correcting Francis data weighting for length and age comps age plots (commit 679ed7c2ecb4b9560b462b95dcd19c08692ba83d). Performed additional cleanup to remove redundant scripts and directories (commits 9d09e3799ea2b7e4df40a517e697249172993199, 1444b51bd919a32782e21dcef075b7cdf44a6dab, b664812d324527bdb357b50d391a6416c5a0e6eb). These changes increase model accuracy, reproducibility, and efficiency of scenario testing, delivering business value in more reliable stock assessments and faster decision support.
May 2025 monthly summary for mcgoodman/widow-assessment-update: Delivered two core features that advance model fidelity and enable robust sensitivity testing for SS3 models. Implemented widow assessment model data weighting enhancements to reflect data source influence by updating weighting parameters in starter.ss and 2025widow.ctl (commit 61c06a47a210a146905b12da3991016912b9139d). Introduced comprehensive sensitivity analysis tooling for SS3 models, including environment setup, base and scenario runs, and generation of comparative plots and tables; consolidated cleanup by removing outdated sensitivity analysis scripts (commits AllSensitivityScript added; AllSensitivityAnalysisScript; and related cleanup). Fixed a critical bug by correcting Francis data weighting for length and age comps age plots (commit 679ed7c2ecb4b9560b462b95dcd19c08692ba83d). Performed additional cleanup to remove redundant scripts and directories (commits 9d09e3799ea2b7e4df40a517e697249172993199, 1444b51bd919a32782e21dcef075b7cdf44a6dab, b664812d324527bdb357b50d391a6416c5a0e6eb). These changes increase model accuracy, reproducibility, and efficiency of scenario testing, delivering business value in more reliable stock assessments and faster decision support.
April 2025 — mcgoodman/widow-assessment-update: Widowfish stock assessment model enhancements implemented to improve reliability and decision support. Consolidated updates fix data loading for age/length composition, refine selectivity parameters across fleets and age/size groups, and add depletion output for sensitivity analysis. A new test script and outputs were added to support robust sensitivity analysis and reproducibility.
April 2025 — mcgoodman/widow-assessment-update: Widowfish stock assessment model enhancements implemented to improve reliability and decision support. Consolidated updates fix data loading for age/length composition, refine selectivity parameters across fleets and age/size groups, and add depletion output for sensitivity analysis. A new test script and outputs were added to support robust sensitivity analysis and reproducibility.

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