

After running an aiR for Review job for the first time, the initial results can be used as feedback for improving the Prompt Criteria. The cycle of examining the results, fine-tuning the Prompt Criteria, then running a new job on the sample documents is known as iterating on the Prompt Criteria.
We recommend the following workflow:
See these related pages:
See these additional resources:
When you select a project from the aiR for Review Projects tab, a dashboard displays showing the project's Prompt Criteria, the list of documents, and controls for editing the project. If the project has been run, it also displays the results.
At the top of the dashboard, the project details strip displays:
On the left side of the dashboard, the Prompt Criteria panel displays tabs that match the project type you chose when creating the project. These tabs contain fields for writing the criteria you want aiR for Review to use when analyzing the documents.
Possible tabs include:
For information on filling out the Prompt Criteria tabs, see Step 2: Writing the Prompt Criteria.
If you want to temporarily clear space on the dashboard, click the Collapse symbol () in the upper right of the Prompt Criteria Panel. To expand the panel, click the symbol again.
For projects that use Issues analysis or Relevance and Key Documents analysis, an aspect selector appears in the upper middle section of the dashboard. This lets you choose which metrics, citations, and other results to view for the analysis results.
For a Relevance and Key Documents analysis, two options appear: one for the field you selected as the Relevant Choice, and one for the field you selected as the Key Document Choice. For Issues analysis, an option appears for every Issues field choice that has choice criteria.
When you select one of the aspects in the bar, the project metrics section and Analysis Results both update to show results related to that aspect. For example, if you choose the key document field, the project metrics section shows how many documents have been coded as key. The Analysis Results grid updates to show predictions, rationales, citations, and all other fields related to whether the document is key. If you choose an issue from the aspect selector, the metrics section and results grid both update to show results related to that specific issue.
For Issues analysis, the issues appear in order according to each choice's Order value. For information on changing the choice order, see Choice detail fields.
In the middle section of the dashboard, the project metrics section shows the results of previous analysis jobs. There are two tabs: one for the current version's most recent results, and one for a list of historical results for all previous versions.
The Version [X] Metrics tab shows metrics divided into three sections: Documents, aiR Analysis, and Conflicts.
In the Documents section:
In the aiR Analysis section:
In the Conflicts section:
Depending which type of results you view, the metrics base their counts on different fields:
For example, if you view results for an issue called Fraud, the aiR Predicted Relevant field will show documents that aiR predicted as relating to Fraud. If you view Key Document results, the aiR Predicted Relevant field will show documents that aiR predicted as being key.
To filter the Analysis Results table below, click on any of the metrics. This narrows the results shown in the table to only documents that are part of the metric. It also auto-selects those documents for the next analysis job. This makes it easier to analyze a subset of the document set, instead of selecting all documents every time.
To remove filtering, click Clear selection underneath the Run button.
The History tab shows results for all previous versions of the Prompt Criteria. This table includes all fields from the Version Metrics tab, sorted into rows by version.
It also includes two additional columns:
For a list of all Version Metrics fields and their definitions, see Version Metrics tab.
In the lower middle section of the dashboard, the Analysis Results section shows a list of all documents in the project. If the documents have aiR for Review analysis results, those results appear beside them in the grid.
The fields that appear in the grid vary depending on what type of analysis was chosen. For a list of all results fields and their definitions, see aiR for Review results.
Note: aiR's predictions do not overwrite the Relevance, Key, or Issues fields chosen during Prompt Criteria setup. Instead, the predictions are held in other fields. This makes it easier to distinguish between human coding choices and aiR's predictions.
To view inline highlighting and citations for an individual document, click on the Control Number. This opens the Viewer and shows results for the selected Prompt Criteria version. For more information on using aiR for Review in the Viewer, see aiR for Review Analysis.
If you check the box beside individual documents in the Analysis Results grid, this manually selects those documents for the next analysis run. You can also filter the Analysis Results grid by clicking the metrics in the Version Metrics section. The number of selected documents is reflected in the Run button's text.
After you have selected the documents you want, you can:
For more information on filtering based on metrics, see Version Metrics tab.
Each aiR for Review project comes with automatic versioning controls, so that you can compare results from running different versions of the Prompt Criteria. Each analysis job that uses a unique set of Prompt Criteria counts as a new version.
When you run aiR for Review analysis for the first time, the Prompt Criteria you use are saved under the name Version 1. This is the initial version of the Prompt Criteria.
After that, if you edit the Prompt Criteria and save your changes, these changes are saved under Version 2. Version 2 is not finalized until you run the analysis, so you can edit the Prompt Criteria as many times as you like. When you have finished editing and are ready to see results, run the analysis again. This finalizes Version 2. Later edits are saved as Version 3 until you run the analysis the third time, then as Version 4 until you run the analysis the fourth time, and so on.
To see dashboard results from a previous version, click the arrow next to the version name in the project details strip. From there, select the version you want to see.
When you select a Prompt Criteria version from the dashboard, this also changes the version results you see when you click on individual documents from the dashboard. For example, if you are viewing results from Version 2, clicking on the Control Number for a document brings you to the Viewer with the results and citations from Version 2. If you select Version 1 on the dashboard, clicking the Control Number for that document brings you to the Viewer with results and citations from Version 1.
When you access the Viewer from other parts of Relativity, it defaults to showing the aiR for Review results from the most recent version of the Prompt Criteria. However, you can change which results appear by using the linking controls on the aiR for Review Jobs tab. For more information, see Managing aiR for Review jobs.
After you run the analysis for the first time on a sample set, use the dashboard to examine the results and refine the Prompt Criteria.
In particular, ask the following questions about each document:
For all of these, if you see something incorrect, make notes on where aiR seems to be confused. Here are the most common sources of confusion:
In general, consider how you would help a human reviewer making the same mistakes. For example, if aiR for Review is having trouble identifying a specific issue, try explaining the criteria for that issue with simpler language.
After you have revised the Prompt Criteria to address any weak points, run the analysis again. Continue refining the Prompt Criteria until aiR accurately predicts the human coding decisions for all test documents in the sample.
Note: aiR for Review only looks at the extracted text of each document. If a human reviewer marked a document as relevant because of an attachment or other criteria beyond the extracted text, aiR for Review will not be able to match that relevance decision.
When aiR for Review accurately matches human coding decisions on the initial sample documents, increase the sample size. Typically, we recommend starting with an initial sample of about 50 documents, then increasing it to include another 50. However, you may find a different number works better for your project.
To increase the aiR for Review job size:
After you have run aiR for Review on the larger sample, continue revising the Prompt Criteria until aiR returns satisfactory results. Continue to increase the job size incrementally until you feel satisfied with the Prompt Criteria. After that, use the refined Prompt Criteria on the larger set of documents. You can do this either from the dashboard, or as a mass operation.
For more information, see the following articles on the Community site:
If you want to run previously refined Prompt Criteria on a set of documents, you have the option of running aiR for Review as a mass operation from the document list page.
To run aiR for Review as a mass operation:
To view and manage jobs that are not part of an existing project, use the aiR for Review Jobs tab. For more information, see Managing aiR for Review jobs.
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