Ensemble

Dataset: espionage

Models

Model Narratives

anthropic10

Round ID: 167
Prompt used:
	Classify an entity based on these refined rules:
	
	DoubleAgent Criteria:
	1. If SecretHandshakeQuality > 70, automatically DoubleAgent
	2. If SecretHandshakeQuality is between 60-70:
	   - Must have AccentThickness less than 30 to be DoubleAgent
	3. If SecretHandshakeQuality is between 55-60:
	   - Must have AccentThickness less than 25 to be DoubleAgent
	
	Loyal Criteria:
	1. If SecretHandshakeQuality ≤ 55, automatically Loyal
	2. If SecretHandshakeQuality is between 55-70:
	   - Must have AccentThickness ≥ 30 to be Loyal
	3. If SecretHandshakeQuality is above 70:
	   - Must have AccentThickness ≥ 35 to be Loyal
	
	Additional Considerations:
	- Use a holistic assessment of both SecretHandshakeQuality and AccentThickness
	- Recognize that the boundary between classifications is not strictly binary
	- Prefer precision in classification over aggressive categorization

Confusion Matrix:
                Predicted DoubleAgent Predicted Loyal     
Actual DoubleAgent                   10                    1
Actual Loyal                       2                    7

Accuracy: 0.850
Precision: 0.833
Recall: 0.909
F1 Score: 0.870

Examples for Correctly predicted DoubleAgent: (Correct answer: DoubleAgent, What the previous set of rules predicted: DoubleAgent)
  Entity Data:
	SecretHandshakeQuality: 84.02795
	AccentThickness: 23.454235


Examples for Falsely predicted Loyal when it should have been DoubleAgent: (Correct answer: DoubleAgent, What the previous set of rules predicted: Loyal)
  Entity Data:
	SecretHandshakeQuality: 69.86503
	AccentThickness: 30.364574


Examples for Falsely predicted DoubleAgent when it should have been Loyal: (Correct answer: Loyal, What the previous set of rules predicted: DoubleAgent)
  Entity Data:
	SecretHandshakeQuality: 71.73181
	AccentThickness: 39.43552


Examples for Correctly predicted Loyal: (Correct answer: Loyal, What the previous set of rules predicted: Loyal)
  Entity Data:
	SecretHandshakeQuality: 50.812286
	AccentThickness: 28.25855


openai

Round ID: 284
Prompt used:
	Rule for Classification:
	1. If SecretHandshakeQuality > 80, classify as DoubleAgent.
	2. If SecretHandshakeQuality > 75 and AccentThickness <= 35, classify as DoubleAgent.
	3. If SecretHandshakeQuality between 65 and 75 and AccentThickness < 30, classify as DoubleAgent.
	4. If AccentThickness >= 35 and SecretHandshakeQuality < 65, classify as Loyal.
	5. If SecretHandshakeQuality < 65, classify as Loyal. 
	
	Note: Override other rules if a condition with SecretHandshakeQuality > 80 applies, to ensure high-quality handshakes are always considered Double Agent regardless of AccentThickness.

Confusion Matrix:
                Predicted DoubleAgent Predicted Loyal     
Actual DoubleAgent                    7                    4
Actual Loyal                       0                    9

Accuracy: 0.800
Precision: 1.000
Recall: 0.636
F1 Score: 0.778

Examples for Correctly predicted DoubleAgent: (Correct answer: DoubleAgent, What the previous set of rules predicted: DoubleAgent)
  Entity Data:
	SecretHandshakeQuality: 80.57122
	AccentThickness: 24.773367


Examples for Falsely predicted Loyal when it should have been DoubleAgent: (Correct answer: DoubleAgent, What the previous set of rules predicted: Loyal)
  Entity Data:
	SecretHandshakeQuality: 69.86503
	AccentThickness: 30.364574


Examples for Correctly predicted Loyal: (Correct answer: Loyal, What the previous set of rules predicted: Loyal)
  Entity Data:
	SecretHandshakeQuality: 68.84351
	AccentThickness: 34.039898


openai10o1

Round ID: 554
Prompt used:
	You are given a single row of data with two fields:
	• SecretHandshakeQuality (numeric)
	• AccentThickness (numeric)
	
	Your task is to predict if this agent is DoubleAgent or Loyal based on the following rules:
	
	1) If SecretHandshakeQuality > 80:
	   Predict DoubleAgent.
	
	2) Else if SecretHandshakeQuality < 58:
	   a) If SecretHandshakeQuality ≥ 55 and AccentThickness < 20, predict DoubleAgent.
	   b) Otherwise, predict Loyal.
	
	3) Else if 58 ≤ SecretHandshakeQuality < 60:
	   a) If AccentThickness < 24, predict DoubleAgent.
	   b) Otherwise, predict Loyal.
	
	4) Else if 60 ≤ SecretHandshakeQuality < 70:
	   a) If SecretHandshakeQuality ≥ 65 and AccentThickness < 31, predict DoubleAgent.
	   b) Else if AccentThickness < 26, predict DoubleAgent.
	   c) Otherwise, predict Loyal.
	
	5) Else (meaning 70 ≤ SecretHandshakeQuality ≤ 80):
	   a) If SecretHandshakeQuality ≥ 75 and AccentThickness < 45, predict DoubleAgent.
	   b) Else if SecretHandshakeQuality ≥ 72 and AccentThickness < 40, predict DoubleAgent.
	   c) Else if AccentThickness < 35, predict DoubleAgent.
	   d) Otherwise, predict Loyal.
	
	Make sure to apply these rules exactly as stated, without any additional interpretation. Only output "DoubleAgent" or "Loyal" as your answer.

Confusion Matrix:
                Predicted DoubleAgent Predicted Loyal     
Actual DoubleAgent                   10                    1
Actual Loyal                       1                    8

Accuracy: 0.900
Precision: 0.909
Recall: 0.909
F1 Score: 0.909

Examples for Correctly predicted DoubleAgent: (Correct answer: DoubleAgent, What the previous set of rules predicted: DoubleAgent)
  Entity Data:
	SecretHandshakeQuality: 67.65863
	AccentThickness: 22.4974


Examples for Falsely predicted Loyal when it should have been DoubleAgent: (Correct answer: DoubleAgent, What the previous set of rules predicted: Loyal)
  Entity Data:
	SecretHandshakeQuality: 69.86503
	AccentThickness: 30.364574


Examples for Falsely predicted DoubleAgent when it should have been Loyal: (Correct answer: Loyal, What the previous set of rules predicted: DoubleAgent)
  Entity Data:
	SecretHandshakeQuality: 72.419624
	AccentThickness: 37.632015


Examples for Correctly predicted Loyal: (Correct answer: Loyal, What the previous set of rules predicted: Loyal)
  Entity Data:
	SecretHandshakeQuality: 68.84351
	AccentThickness: 34.039898


Ensemble Confusion Matrix

Predicted +Predicted -
Actual +101
Actual -18

Accuracy 0.900, Precision 0.909, Recall 0.909, F1 0.909