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Akram Zaytar (Akramz) merged 2 commits into from
Nov 2, 2026
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Add explainer video to README #14

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add explainer video
calebrob6 Nov 2, 2026
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Reorganize README and update audit output image
calebrob6 Nov 2, 2026
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6 changes: 5 additions & 1 deletion README.md
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Expand Up @@ -2,7 +2,9 @@

PaPPI (Protocol-aware Prediction-Powered Inference) estimates a crop map's macro-F1 or accuracy across its deployment area, with a confidence interval. It uses biased field labels and unlabeled deployment points. Crop maps are usually evaluated on labels collected near roads or in a few survey areas, so their reported scores can overstate performance across the area they cover.

![audit output](docs/audit_output.svg)
Watch the [PaPPI explainer video](https://opendata.aiforgood.ai/videos/pappi-ppi-explainer.mp4).

https://github.com/user-attachments/assets/0cdb3407-373c-40a7-b2dc-8b19ca6da28c

## Setup

Expand Down Expand Up @@ -44,6 +46,8 @@ Audit a trained model with labeled rows that it has never seen:
$ pappi audit test_and_deploy.csv --model my_model.joblib
```

![audit output](docs/audit_output.svg)

## Input

Each row represents one sample. Rows with a `label` form the labeled set. Rows with an empty `label` must be a uniform sample of the deployment population. `--label` changes the label column name, and `--features` changes the feature-column prefix.
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