Remove pages workflow and update docs

Author: rollingstorms

.github/workflows/pages.yml

@@ -5,6 +5,7 @@ __pycache__/
 .pytest_cache/
 .mypy_cache/
 .ruff_cache/
+.cache/ 
 
 # Virtual environments
 .venv/

.gitignore

@@ -4,6 +4,20 @@ A compact operating profile plot for binary classifiers: stacked score histogram
 
 ![Opproplot hero](assets/opproplot_hero.png)
 
+## What is an Operating Profile Plot?
+
+An Operating Profile Plot (Opproplot) is a unified visualization for binary classifiers that shows how a model behaves across every possible decision threshold. It combines:
+- a stacked histogram of predicted scores for positives vs. negatives
+- threshold-dependent performance metrics such as Recall (TPR) and False Positive Rate (FPR)
+- computed at the midpoint of each score bin, treating each as a candidate threshold
+
+This creates a complete operating profile of the model in a single view — letting you see where the model is confident, where the classes overlap, and how performance changes as you move the threshold.
+
+Rather than switching between ROC curves, PR curves, histograms, and calibration plots, Opproplot places the score distribution and the operating characteristics on the same axis, making it easy to:
+- identify thresholds with optimal trade-offs
+- diagnose where errors occur in score space
+- communicate model quality visually and quickly
+
 ## Why Opproplot
 
 - See score separation between classes directly.