```python
# ProBERT Quick Inference Example
# Zero dependencies beyond transformers + torch

from transformers import AutoModelForSequenceClassification, AutoTokenizer
import torch

# Load frozen model
model = AutoModelForSequenceClassification.from_pretrained("collapseindex/ProBERT-1.0")
tokenizer = AutoTokenizer.from_pretrained("collapseindex/ProBERT-1.0")

def score_text(text: str) -> dict:
    """Score text for rhetorical patterns"""
    inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=128)
    
    with torch.no_grad():
        outputs = model(**inputs)
    
    probs = torch.softmax(outputs.logits, dim=1)[0]
    
    labels = ["process_clarity", "rhetorical_confidence", "scope_blur"]
    scores_dict = {label: float(probs[i]) for i, label in enumerate(labels)}
    prediction = labels[torch.argmax(probs).item()]
    
    # Confidence: max probability
    confidence = float(probs.max())
    
    # Coherence: margin between top 2 predictions (lower = less clear decision)
    sorted_probs = torch.sort(probs, descending=True)[0]
    coherence = float(sorted_probs[0] - sorted_probs[1])
    
    return {
        **scores_dict,
        "prediction": prediction,
        "confidence": confidence,
        "coherence": coherence
    }

# Test examples
examples = [
    "This revolutionary AI will transform your business and guarantee results.",
    "To implement binary search: 1. Define left and right pointers. 2. Calculate mid. 3. Compare value. If less, move right pointer.",
    "Trust your intuition and embrace the cosmic energy flowing through all things.",
]

for text in examples:
    scores = score_text(text)
    print(f"\nText: {text[:60]}...")
    print(f"Prediction: {scores['prediction']}")
    print(f"  • Process Clarity:        {scores['process_clarity']:.1%}")
    print(f"  • Rhetorical Confidence:  {scores['rhetorical_confidence']:.1%}")
    print(f"  • Scope Blur:             {scores['scope_blur']:.1%}")
    print(f"Confidence: {scores['confidence']:.1%}")
    print(f"Coherence:  {scores['coherence']:.1%} (decision clarity)")
```

**Output Example:**
```
Text: This revolutionary AI will transform your business and guarantee r...
Prediction: rhetorical_confidence
  • Process Clarity:        11.5%
  • Rhetorical Confidence:  67.2%
  • Scope Blur:             21.3%
Confidence: 67.2%
Coherence:  45.9% (decision clarity)

Text: To implement binary search: 1. Define left and right pointers. 2....
Prediction: process_clarity
  • Process Clarity:        79.7%
  • Rhetorical Confidence:  12.3%
  • Scope Blur:             8.0%
Confidence: 79.7%
Coherence:  67.4% (decision clarity)

Text: Trust your intuition and embrace the cosmic energy flowing through all things.
Prediction: scope_blur
  • Process Clarity:        14.2%
  • Rhetorical Confidence:  25.3%
  • Scope Blur:             60.5%
Confidence: 60.5%
Coherence:  35.2% (decision clarity)
```