Analyze the following call transcript and provide structured analysis.

## CALL METADATA
- Call ID: {call_id}
- Duration: {duration_sec} seconds
- Queue: {queue}

## OBSERVED EVENTS (Pre-detected)
{observed_events}

## TRANSCRIPT
{transcript}

## TAXONOMY - LOST SALES DRIVERS
{lost_sales_taxonomy}

## TAXONOMY - POOR CX DRIVERS
{poor_cx_taxonomy}

## INSTRUCTIONS

1. Determine the call outcome from: SALE_COMPLETED, SALE_LOST, CANCELLATION_SAVED, CANCELLATION_COMPLETED, INQUIRY_RESOLVED, INQUIRY_UNRESOLVED, COMPLAINT_RESOLVED, COMPLAINT_UNRESOLVED, TRANSFER_OUT, CALLBACK_SCHEDULED, UNKNOWN

2. Identify lost_sales_drivers (if applicable):
   - Use ONLY codes from the Lost Sales taxonomy
   - Each driver MUST have evidence_spans with exact quotes and timestamps
   - Assign confidence based on evidence strength

3. Identify poor_cx_drivers (if applicable):
   - Use ONLY codes from the Poor CX taxonomy
   - Each driver MUST have evidence_spans with exact quotes and timestamps
   - Assign confidence based on evidence strength

4. For OTHER_EMERGENT, provide a proposed_label describing the new cause.

Respond with JSON only:

```json
{
  "outcome": "SALE_LOST",
  "lost_sales_drivers": [
    {
      "driver_code": "PRICE_TOO_HIGH",
      "confidence": 0.85,
      "evidence_spans": [
        {
          "text": "Es demasiado caro para mí",
          "start_time": 45.2,
          "end_time": 47.8,
          "speaker": "customer"
        }
      ],
      "reasoning": "Customer explicitly states price is too high"
    }
  ],
  "poor_cx_drivers": [
    {
      "driver_code": "LONG_HOLD",
      "confidence": 0.90,
      "evidence_spans": [
        {
          "text": "Llevo esperando mucho tiempo",
          "start_time": 120.5,
          "end_time": 123.1,
          "speaker": "customer"
        }
      ],
      "reasoning": "Customer complains about wait time"
    }
  ]
}
```