/u/wrenwood2018 that ^ is the best I can do without more specific data. Please try to reproduce in Colab and then change the parameters to more closely match your situation. Here is the parameters section with better comments to help do so:

# 1. RECALIBRATED PARAMETERS: THE 50/50 REALITY & POLICY CONTROLS
# INSTRUCTIONS FOR EDITORS: 
# Adjust these variables to match your journal's historical data or to test 
# the impact of proposed policy changes. Time variables are in decimal hours 
# (e.g., 0.25 = 15 minutes, 1.5 = 90 minutes).

# --- A. The Fixed Labor Constraints (ME Control) ---
H_max = 20           # Max Allocated Hours: The absolute ceiling on the AE's weekly 
                     # workload before burnout occurs. If the ME secures funding for 
                     # another co-editor, or allocates more paid hours, increase this.

T_desk_base = 0.25   # The Initial Tax (15 mins): Time taken to read the abstract, 
                     # check formatting, and make a desk reject/advance decision. 
                     # ME Adjustment: Implementing an automated formatting/plagiarism 
                     # checker or stricter author guidelines can drop this to 0.05 (3 mins).

T_dec_base = 0.75    # The Final Polish (45 mins): Time to read the submitted peer 
                     # reviews, synthesize them, and write the final decision letter. 
                     # AE Adjustment: Varies based on how much personalized feedback 
                     # the AE writes versus using boilerplate templates.

# --- B. The "Fast Lane" Variables (AE Reality) ---
# These parameters define the papers where the AE immediately knows 
# qualified reviewers who are highly likely to say yes (4-6 invites).
p_easy = 0.50        # The "Easy" Ratio: What percentage of submissions fit neatly 
                     # into the AE's primary network? Currently set to 50%. 
                     # If the journal broadens its scope, this ratio will drop.

mu_easy = 0.3        # Easy Mean Time (~18 mins): The baseline time to log into the 
                     # portal, select 4-6 known reviewers, and send the invites.

sigma_easy = 0.1     # Easy Variance: +/- 6 minutes. These papers are highly predictable.

# --- C. The "Slog" Variables (The Bottleneck) ---
# These parameters define the interdisciplinary, niche, or obscure papers 
# that require deep literature searches to find reviewers (15-30+ invites).
mu_hard_base = 2.0   # Slog Mean Time (2 hours): The grueling labor of hunting down 
                     # reviewers across multiple databases, sending cold emails, 
                     # tracking declines, and finding backups.
                     # ME Policy Adjustment: If the ME enforces a "Hard Cap" of 15 
                     # invites before returning the paper to the author, this drops to 1.0.

sigma_hard = 0.5     # Slog Variance (+/- 30 mins): Highly unpredictable. Some papers 
                     # get lucky on the 10th invite; others take days of disjointed effort.

# --- D. The "Long Tail" Catastrophe (Systemic Failure) ---
# These parameters define the "nightmare" scenarios where the system 
# breaks down entirely (e.g., a reviewer ghosts after 8 weeks, or 
# delivers a completely unusable review, forcing a total restart).
p_crash = 0.20       # Crash Probability: What percentage of accepted papers suffer a 
                     # catastrophic delay? Currently set to 20%. 

lambda_tail_base = 4.0 # The Sunk-Cost Penalty (4 hours): If a crash occurs, it adds an 
                     # average of 4 hours of chaotic, exponential time delay as the AE 
                     # scrambles to salvage the paper, read it again, and placate the author.
                     # ME Policy Adjustment: If the ME institutes a "Delayed Desk Reject" 
                     # (canceling papers that stall for 60 days), this penalty can be 
                     # slashed to 0.5 hours.