System: You are a helpful and precise assistant in checking the quality of the answer.
User: We would like to request your feedback on the performance of the response of the assistant to the user instruction displayed below. In the feedback, I want you to rate the quality of the response in these 3 categories according to each scoring rubric:

Logical Robustness: Does the model ensure general applicability and avoid logical contradictions in its reasoning steps for an instruction that requires step-by-step logical process? This includes the consideration of edge cases for coding and mathematical problems, and the absence of any counterexamples.
Score 1: The logic of the model's response is completely incoherent.
Score 2: The model's response contains major logical inconsistencies or errors.
Score 3: The model's response contains some logical inconsistencies or errors, but they are not significant.
Score 4: The model's response is logically sound, but it does not consider some edge cases.
Score 5: The model's response is logically flawless and it takes into account all potential edge cases.
Logical Correctness: Is the final answer provided by the response logically accurate and correct for an instruction that has a deterministic answer?
Score 1: The model's final answer is completely incorrect and lacks sound reasoning.
Score 2: The model's final answer contains significant errors that critically undermine its correctness.
Score 3: The model's final answer includes inaccuracies that require considerable effort to correct.
Score 4: The model's final answer contains minor errors, which are easy to rectify and do not significantly impact its overall correctness.
Score 5: The model's final answer is completely accurate and sound.
Logical Efficiency: Is the response logically efficient? The logic behind the response should have no redundant step, remaining simple and efficient. For tasks involving coding, the proposed solution should also consider time complexity.
Score 1: The logic behind the response is significantly inefficient and redundant, necessitating a complete reorganization of logic for clarity and efficiency.
Score 2: The logic of the response lacks efficiency and conciseness, requiring a substantial reorganization for better optimization.
Score 3: The logic of the response is not efficient enough, necessitating major edits for improved optimization.
Score 4: The logic of the response is largely efficient, but it still has some redundant steps. It could be handled from minor edits for better optimization.
Score 5: The logic of the response is optimally efficient, requiring no further optimization.
[Instruction]
Given a sorted linked list, delete all nodes that have duplicate numbers, leaving only distinct numbers from the original list.

Example 1:

Input: 1->2->3->3->4->4->5
Output: 1->2->5
Example 2:

Input: 1->1->1->2->3
Output: 2->3

[Ground truth Answer]
# Definition for singly-linked list.
# class ListNode(object):
#     def __init__(self, x):
#         self.val = x
#         self.next = None

class Solution(object):
    def deleteDuplicates(self, head):
        """
        :type head: ListNode
        :rtype: ListNode
        """
        if not head:
                return None

        result = ListNode(0)
        ans = result
        curr = head
        while curr:
                value = curr.val
                count = 0
                while curr and curr.val == value:
                        curr = curr.next
                        count += 1
                if count == 1:
                        result.next = ListNode(value)
                        result = result.next
        return ans.next

[Assistant's Response]
To solve the problem of removing all nodes with duplicate values from a sorted linked list, we can utilize a systematic approach that leverages a dummy node to simplify the handling of edge cases. Here's a structured explanation of the algorithm, along with an implementation in Python.

### Steps to Remove Duplicates

1. **Initialize a Dummy Node**: Create a dummy node that points to the head of the linked list. This helps manage cases where the head itself might be a duplicate.

2. **Set Up Pointers**: Use two pointers: `prev`, initialized to the dummy node, and `current`, initialized to the head of the list.

3. **Traverse the List**: Iterate through the list using the `current` pointer.

4. **Identify Duplicates**: For each node, check if it has a duplicate by comparing it to the next node. If duplicates are detected (i.e., `current.val` equals `current.next.val`), skip all nodes with that value.

5. **Remove Duplicates**: If duplicates are found, link the `prev` node to the node that follows the last duplicate. If no duplicates are found, simply move the `prev` pointer to the `current` node.

6. **Advance the Current Pointer**: Move the `current` pointer to the next node in the list.

7. **Return the Result**: Finally, return the modified list starting from the node next to the dummy node.

### Python Implementation

Here’s the Python code that implements the above logic:

```python
class ListNode:
    def __init__(self, val=0, next=None):
        self.val = val
        self.next = next

def deleteDuplicates(head: ListNode) -> ListNode:
    # Create a dummy node
    dummy = ListNode(0)
    dummy.next = head
    
    # Initialize prev to dummy and current to head
    prev = dummy
    current = head
    
    while current:
        # Check if current node has a duplicate
        if current.next and current.val == current.next.val:
            # Skip all nodes with the same value
            while current.next and current.val == current.next.val:
                current = current.next
            # Link prev to the node after the last duplicate
            prev.next = current.next
        else:
            # No duplicates, move prev to current
            prev = current
        
        # Move current to the next node
        current = current.next
    
    return dummy.next

# Example usage:
# Construct the linked list 1->2->3->3->4->4->5
head = ListNode(1, ListNode(2, ListNode(3, ListNode(3, ListNode(4, ListNode(4, ListNode(5)))))))

# Call the function
result = deleteDuplicates(head)

# Print the result list
while result:
    print(result.val, end="->" if result.next else "")
    result = result.next
```

### Example Outputs

1. For the input list `1->2->3->3->4->4->5`, the output will be `1->2->5`.
2. For the input list `1->1->1->2->3`, the output will be `2->3`.

This approach efficiently removes all duplicates from a sorted linked list while maintaining the order of distinct elements. The time complexity is O(n), where n is the number of nodes in the list, making it efficient for this problem.

[The End of Assistant's Response]

Please give feedback on the assistant's responses. Also, provide the assistant with a score on a scale of 1 to 5 for each category, where a higher score indicates better overall performance. Make sure to give feedback or comments for each category first and then write the score for each category. Only write the feedback corresponding to the scoring rubric for each category. The scores of each category should be orthogonal, indicating that 'Efficiency of User Alignment' should not be considered for 'Readability of User Alignment' category, for example. 

Lastly, return a Python dictionary object that has skillset names as keys and the corresponding scores as values.

[System]



Assistant: