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- Clone the **[alb-2024-diagnostic](https://github.com/PacificCommunity/ofp-sam-alb-2024-diagnostic)** repository or download as **[main.zip](https://github.com/PacificCommunity/ofp-sam-alb-2024-diagnostic/archive/refs/heads/main.zip)** file
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Download SPALB 2024 model ensemble results:
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- The **[alb-2024-model-ensemble](https://github.com/PacificCommunity/ofp-sam-alb-2024-model-ensemble)** repository includes a **[alb-2024-model-ensemble-results.zip](https://github.com/PacificCommunity/ofp-sam-alb-2024-model-ensemble/releases/download/file/alb-2024-model-ensemble-results.zip)** file
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## Uncertainty
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The SPALB 2024 assessment uncertainty was estimated using a Monte Carlo model ensemble approach in which 100 models incorporated uncertainty in average natural mortality, stock-recruitment steepness and
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estimation error for individual models:
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## Model ensemble results
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The [alb-2024-model-ensemble-results.zip](https://github.com/PacificCommunity/ofp-sam-alb-2024-model-ensemble/releases/download/file/alb-2024-model-ensemble-results.zip) file contains all files necessary to run or browse the SPALB 2024 model ensemble.
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The ensemble models are run from a par file, as described in the corresponding `doitall.sh` script.
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The final par and rep files are consistently named `09.par` and `plot-09.par.rep` to facilitate harvesting results from across the 100 ensemble models.
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```
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## Estimating uncertainty
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See also Section 8, Section 10.6 and Table 9 in the SPALB 2024 stock assessment [report](https://meetings.wcpfc.int/node/23119).
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The script requires the FLR and FLR4MFCL packages:
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