import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.ArrayList;
import java.util.Arrays;


public class GooglersDancer {

	/**
	 * @param args
	 * @throws IOException
	 */
	public static void main(String[] args) throws IOException {
		// TODO Auto-generated method stub
		InputStreamReader converter = new InputStreamReader(System.in);
		BufferedReader in = new BufferedReader(converter);
		if (in == null) {
		      return;
		    }
		String numTest = in.readLine();
		int maxCases = Integer.valueOf(numTest);
		for(int i=1;i<= maxCases;i++){
			String linea = in.readLine();
			String[] datos = linea.split(" ");
			Integer googlers = Integer.valueOf(datos[0]);
			Integer sospechosos = Integer.valueOf(datos[1]);
			Integer p = Integer.valueOf(datos[2]);
			Integer puntuacion;
			Integer personas = 0;
			ArrayList<Integer> puntuaciones = new ArrayList<Integer>();
			for(int j=0;j<googlers;j++){
				puntuacion = Integer.valueOf(datos[3+j]);
				puntuaciones.add(puntuacion);
			}
			Integer[] pOrdenado = null;
			pOrdenado = (Integer[]) puntuaciones.toArray(new Integer[puntuaciones.size()]);
			Arrays.sort(pOrdenado);
			int j;
			for(j=pOrdenado.length-1;j>=0;j--){
				if(pOrdenado[j] >= p*3-2){
					personas += 1;
				}else{
					break;
				}
			}
			int posibles = j+1-sospechosos;
			for(;j>=posibles && j>= 0;j--){
				if(pOrdenado[j] >= p*3-4 && pOrdenado[j] > p){
					personas += 1;
				}else{
					break;
				}
			}
			System.out.println("Case #"+i+": "+personas);
		}
	}

}

package fixjava;

import java.util.ArrayList;
import java.util.concurrent.Callable;

/** Parallel quicksort (inefficient initially, doubles the number of threads at each pivot) */
public class ParallelQuicksort<T extends Comparable<T>> implements Callable<Void> {

	private ArrayList<T> list;
	private ParallelWorkQueueDynamic workQueue;

	// Have to create own stack because otherwise we can get stack overflow using normal recursion 
	private ArrayList<Integer> loStack = new ArrayList<Integer>();
	private ArrayList<Integer> hiStack = new ArrayList<Integer>();

	private ParallelQuicksort(ArrayList<T> list, int lo, int hi, ParallelWorkQueueDynamic workQueue) {
		this.list = list;
		this.workQueue = workQueue;
		push(lo, hi);
	}

	private void push(int lo, int hi) {
		loStack.add(lo);
		hiStack.add(hi);
	}

	private void exch(int i, int j) {
		T tmp = list.get(i);
		list.set(i, list.get(j));
		list.set(j, tmp);
	}

	private int partition(int lo, int hi) {
		exch(lo, lo + (hi - lo) / 2);
		int i = lo;
		int j = hi + 1;
		while (true) {
			for (int idxLo = lo; list.get(++i).compareTo(list.get(idxLo)) < 0 && i != hi;)
				;
			for (int idxLo = lo; list.get(idxLo).compareTo(list.get(--j)) < 0 && j != lo;)
				;
			if (i >= j)
				break;
			exch(i, j);
		}
		exch(lo, j);
		return j;
	}

	@Override
	public Void call() {
		int stackSize = 1;
		while ((stackSize = loStack.size()) > 0) {
			// Pop top of stack
			int lo = loStack.get(stackSize - 1);
			int hi = hiStack.get(stackSize - 1);
			loStack.remove(stackSize - 1);
			hiStack.remove(stackSize - 1);

			// Go up a stack frame when hi <= lo
			if (hi > lo) {

				// Partition
				final int j = partition(lo, hi);

				if (j - lo > 1000 && workQueue.hasIdleWorkers()) {
					// If there is enough work to do to justify multithreading and if there are idle threads,
					// fork and recurse on one one side of partition on a different thread
					workQueue.enqueueWork(new ParallelQuicksort<T>(list, lo, j - 1, workQueue));

					// Execute other half of subdivision in this thread
					push(j + 1, hi);

				} else {
					// Not worth forking another thread (not enough work to do), or not enough free workers

					push(lo, j - 1);
					push(j + 1, hi);
				}
			}
		}
		return null;
	}

	// ---------------------------------------------------------

	public static <T extends Comparable<T>> void sortInPlace(ArrayList<T> list, int numThreads) {
		ParallelWorkQueueDynamic workQueue = new ParallelWorkQueueDynamic(numThreads);
		workQueue.enqueueWork(new ParallelQuicksort<T>(list, 0, list.size() - 1, workQueue));
		workQueue.waitForAllWorkersToQuit();
		workQueue.shutdown();
	}
}
