Ensemble

Dataset: titanic

Models

Model Narratives

anthropic

Round ID: 84
Prompt used:
	Predict treatment outcome using these decision rules:
	
	1. Histogen_Complex Delta:
	   - FAILURE if:
	     a) Treatment_Months > 90 AND TcQ_mass < 9000
	     b) Treatment_Months < 60 AND TcQ_mass > 7500
	     c) Genetic_Class_B_Matches > 1 AND Treatment_Months > 120
	
	2. Histogen_Complex Beta:
	   - SUCCESS more likely if:
	     a) TcQ_mass > 40000
	     b) Genetic_Class_A_Matches > 1
	     c) Treatment_Months between 100-150
	
	3. Histogen_Complex Omicron:
	   - FAILURE more likely if:
	     a) Treatment_Months > 150
	     b) TcQ_mass > 12000
	
	4. Additional Considerations:
	   - Higher number of genetic matches suggests better treatment resilience
	   - Cohort (Melbourne/Delhi) may modify baseline predictions
	   - Sex can be a secondary modifier of outcome probability
	
	Evaluation Steps:
	1. Identify Histogen_Complex
	2. Apply complex-specific rules
	3. Check genetic match and treatment duration
	4. Consider TcQ_mass thresholds
	5. Make final prediction with nuanced confidence

Confusion Matrix:
                Predicted Failure    Predicted Success   
Actual Failure                    14                   14
Actual Success                     5                   18

Accuracy: 0.627
Precision: 0.737
Recall: 0.500
F1 Score: 0.596

Examples for Correctly predicted Failure: (Correct answer: Failure, What the previous set of rules predicted: Failure)
  Entity Data:
	Histogen_Complex: Delta
	Sex: female
	Treatment_Months: 90.0
	Genetic_Class_A_Matches: 1
	Genetic_Class_B_Matches: 1
	TcQ_mass: 7895.8
	Cohort: Melbourne


Examples for Falsely predicted Success when it should have been Failure: (Correct answer: Failure, What the previous set of rules predicted: Success)
  Entity Data:
	Histogen_Complex: Omicron
	Sex: female
	Treatment_Months: 75.0
	Genetic_Class_A_Matches: 2
	Genetic_Class_B_Matches: 3
	TcQ_mass: 41579.2
	Cohort: Delhi


Examples for Falsely predicted Failure when it should have been Success: (Correct answer: Success, What the previous set of rules predicted: Failure)
  Entity Data:
	Histogen_Complex: Delta
	Sex: male
	Treatment_Months: 89.09735294117647
	Genetic_Class_A_Matches: 1
	Genetic_Class_B_Matches: 1
	TcQ_mass: 7879.2
	Cohort: Lisbon


Examples for Correctly predicted Success: (Correct answer: Success, What the previous set of rules predicted: Success)
  Entity Data:
	Histogen_Complex: Beta
	Sex: female
	Treatment_Months: 111.0
	Genetic_Class_A_Matches: 2
	Genetic_Class_B_Matches: 2
	TcQ_mass: 52554.200000000004
	Cohort: Melbourne

openai

Round ID: 342
Prompt used:
	Use the following rules to classify the data entries as 'Failure' or 'Success':
	
	1. If 'Treatment_Months' > 100 and 'TcQ_mass' < 10,000, classify as 'Failure'.
	2. If 'Histogen_Complex' is 'Omicron' and 'TcQ_mass' < 20,000, classify as 'Failure'.
	3. If 'Genetic_Class_A_Matches' + 'Genetic_Class_B_Matches' >= 4 and 'TcQ_mass' > 50,000, classify as 'Success'.
	4. For entities in Cohort 'Delhi' with 'Treatment_Months' > 150 and 'TcQ_mass' < 15,000, classify as 'Failure'.
	5. For 'Histogen_Complex' 'Beta' or 'Delta' and 'TcQ_mass' > 70,000, classify as 'Success' unless 'Treatment_Months' < 10.
	6. If 'Histogen_Complex' is 'Beta', 'TcQ_mass' > 200,000, and 'Treatment_Months' < 100, classify as 'Failure'.
	7. If 'Histogen_Complex' is 'Delta' and 'TcQ_mass' < 8,000, classify as 'Failure'.
	
	Classify based on these rules, and in cases not aligned to any rule above, use 'Failure' as the default classification.

Confusion Matrix:
                Predicted Failure    Predicted Success   
Actual Failure                    27                    1
Actual Success                    19                    4

Accuracy: 0.608
Precision: 0.587
Recall: 0.964
F1 Score: 0.730

Examples for Correctly predicted Failure: (Correct answer: Failure, What the previous set of rules predicted: Failure)
  Entity Data:
	Histogen_Complex: Delta
	Sex: female
	Treatment_Months: 63.0
	Genetic_Class_A_Matches: 1
	Genetic_Class_B_Matches: 1
	TcQ_mass: 7250.0
	Cohort: Melbourne


Examples for Falsely predicted Success when it should have been Failure: (Correct answer: Failure, What the previous set of rules predicted: Success)
  Entity Data:
	Histogen_Complex: Beta
	Sex: female
	Treatment_Months: 132.0
	Genetic_Class_A_Matches: 3
	Genetic_Class_B_Matches: 1
	TcQ_mass: 90000.0
	Cohort: Lisbon


Examples for Falsely predicted Failure when it should have been Success: (Correct answer: Success, What the previous set of rules predicted: Failure)
  Entity Data:
	Histogen_Complex: Omicron
	Sex: male
	Treatment_Months: 99.0
	Genetic_Class_A_Matches: 2
	Genetic_Class_B_Matches: 3
	TcQ_mass: 27750.0
	Cohort: Melbourne


Examples for Correctly predicted Success: (Correct answer: Success, What the previous set of rules predicted: Success)
  Entity Data:
	Histogen_Complex: Beta
	Sex: male
	Treatment_Months: 117.0
	Genetic_Class_A_Matches: 2
	Genetic_Class_B_Matches: 2
	TcQ_mass: 79650.0
	Cohort: Melbourne

openailong

Round ID: 140
Prompt used:
	Based on the analysis of the dataset, please follow these explicit and specific rules to predict the outcome:
	
	1. **Treatment Months Rule:**  
	   - If 'Treatment_Months' is less than 10, predict 'Success'.  
	   - If 'Treatment_Months' is between 10 and 65:  
	       - If 'Histogen_Complex' is 'Omega' and 'Genetic_Class_A_Matches' is at least 2, predict 'Success'.  
	       - If 'Histogen_Complex' is 'Omicron' and 'Genetic_Class_A_Matches' is 1 or less, predict 'Failure'.  
	       - If 'Histogen_Complex' is 'Delta', predict 'Failure' regardless of 'Genetic_Class_A_Matches'.  
	       - Otherwise, predict 'Failure'.  
	   - If 'Treatment_Months' is between 66 and 89:  
	       - If 'Histogen_Complex' is 'Delta', predict 'Failure'.  
	       - If 'Histogen_Complex' is not 'Delta' and 'Genetic_Class_A_Matches' is less than 2, predict 'Failure'.  
	       - If 'Histogen_Complex' is not 'Delta' and 'Genetic_Class_A_Matches' is at least 2, predict 'Success'.  
	   - If 'Treatment_Months' is 90 or more:  
	       - If 'Histogen_Complex' is 'Delta' and 'TcQ_mass' is below 30000, predict 'Failure'.  
	       - If 'Cohort' is 'Melbourne', predict 'Failure' unless 'TcQ_mass' is above 30000 and 'Genetic_Class_A_Matches' is at least 3.  
	       - For 'Cohort: Lisbon', predict 'Failure' if 'Treatment_Months' is greater than 150 with no other criteria met.  
	       - Predict 'Success' only if 'TcQ_mass' is below 15000 or if 'Histogen_Complex' is not 'Delta' and 'Genetic_Class_A_Matches' is above 2.  
	
	2. **TcQ_mass Criteria:**  
	   - If 'TcQ_mass' is below 16000 and 'Histogen_Complex' is 'Delta', predict 'Failure'.  
	   - If 'TcQ_mass' is between 16000 and 30000 and 'Treatment_Months' is over 80, predict 'Success' only if 'Genetic_Class_A_Matches' is at least 2.  
	   - If 'TcQ_mass' is 30000 or more and 'Genetic_Class_A_Matches' is at least 2, predict 'Success'.  
	
	3. **Genetic Class Match Rule:**  
	   - If 'Genetic_Class_A_Matches' is 5 or more, predict 'Success'.  
	   - If 'Genetic_Class_A_Matches' is equal to 1 or the total with 'Genetic_Class_B_Matches' is less than 3, predict 'Failure'.  
	   - If 'Genetic_Class_A_Matches' is between 2 and 4 and 'Histogen_Complex' is not 'Delta', predict 'Success' only if 'TcQ_mass' is above 20000.  
	
	4. **Cohort Influence:**  
	   - For 'Cohort: Melbourne', predict 'Success' if 'TcQ_mass' is above 30000 and 'Treatment_Months' is below 150; otherwise, predict 'Failure'.  
	   - For 'Cohort: Delhi', predict 'Failure' if 'Treatment_Months' exceeds 105 and 'TcQ_mass' is below 20000 regardless of matches.  
	   - For 'Cohort: Lisbon', predict 'Success' only if 'Genetic_Class_A_Matches' is 2 or more and 'TcQ_mass' is above 30000.  
	
	5. **New Enhanced Rule About Histogen Complex:**  
	   - If 'Histogen_Complex' is 'Beta' and 'TcQ_mass' is above 50000, predict 'Success' without additional conditions.  
	   - If 'Histogen_Complex' is 'Beta' and 'Genetic_Class_A_Matches' is 3 or more, predict 'Success' to reduce false negatives from previously caught errors.  
	
	6. **Fallback Condition:**  
	   - If no other rules apply, predict 'Failure' to minimize false positives.

Confusion Matrix:
                Predicted Failure    Predicted Success   
Actual Failure                    24                    4
Actual Success                    12                   11

Accuracy: 0.686
Precision: 0.667
Recall: 0.857
F1 Score: 0.750

Examples for Correctly predicted Failure: (Correct answer: Failure, What the previous set of rules predicted: Failure)
  Entity Data:
	Histogen_Complex: Delta
	Sex: female
	Treatment_Months: 84.0
	Genetic_Class_A_Matches: 1
	Genetic_Class_B_Matches: 1
	TcQ_mass: 56495.8
	Cohort: Melbourne


Examples for Falsely predicted Success when it should have been Failure: (Correct answer: Failure, What the previous set of rules predicted: Success)
  Entity Data:
	Histogen_Complex: Beta
	Sex: female
	Treatment_Months: 89.09735294117647
	Genetic_Class_A_Matches: 1
	Genetic_Class_B_Matches: 1
	TcQ_mass: 221779.2
	Cohort: Melbourne


Examples for Falsely predicted Failure when it should have been Success: (Correct answer: Success, What the previous set of rules predicted: Failure)
  Entity Data:
	Histogen_Complex: Omicron
	Sex: male
	Treatment_Months: 99.0
	Genetic_Class_A_Matches: 2
	Genetic_Class_B_Matches: 3
	TcQ_mass: 27750.0
	Cohort: Melbourne


Examples for Correctly predicted Success: (Correct answer: Success, What the previous set of rules predicted: Success)
  Entity Data:
	Histogen_Complex: Omicron
	Sex: male
	Treatment_Months: 42.0
	Genetic_Class_A_Matches: 2
	Genetic_Class_B_Matches: 1
	TcQ_mass: 30070.8
	Cohort: Delhi

Ensemble Confusion Matrix

Predicted +Predicted -
Actual +244
Actual -1211

Accuracy 0.686, Precision 0.667, Recall 0.857, F1 0.750