▸case-01 I have a computational model with 12 input parameters and want to perform a global sensitivity analysis using the Morris method. Please design the trajectory grid, calculate the elementary effects (mean and standard deviation) for each factor, and provide a clear ranking of parameter importance to identify which inputs can be fixed without affecting output variance. | fail→fail | 30,023 | 14,503 | -52% | 1 | 1 | 0% | 5,014 | 663 | -87% | 0 | 0 | — |
▸case-02 Could you run a Morris screening analysis on my hydrologic model parameters? I need you to evaluate the trajectories across the parameter space, compute the elementary effect metrics, and output a prioritized list comparing direct and interactive effects among the inputs. | fail→fail | 33,231 | 61,635 | +85% | 1 | 1 | 0% | 5,521 | 814 | -85% | 0 | 0 | — |
▸case-03 We need to conduct a preliminary screening on our simulation parameters to reduce dimensionality. Please carry out a Morris elementary effects analysis, computing the sensitivity measures for all factors, and produce a structured summary ranking the parameters from most to least influential. | fail→fail | 22,035 | 20,002 | -9% | 1 | 1 | 0% | 3,193 | 631 | -80% | 0 | 0 | — |
▸case-04 I am writing a paper on global sensitivity analysis and need an explanation of how elementary effects are defined in the Morris method. Please provide the mathematical formula for an elementary effect EE_i given a trajectory step delta, and explain the statistical significance of mu versus mu_star. | pass→pass | 19,050 | 21,813 | +15% | 1 | 1 | 0% | 2,866 | 3,177 | +11% | 0 | 0 | — |
▸case-05 We want to perform a variance-based Sobol sensitivity analysis on our 4-parameter chemical reaction rate model. Please calculate the first-order and total-order Sobol sensitivity indices for all parameters using 1000 Monte Carlo samples. | fail→pass | 36,315 | 74,830 | +106% | 1 | 1 | 0% | 2,720 | 8,366 | +208% | 0 | 0 | — |
▸case-06 I already ran a screening analysis elsewhere and have the final results: Parameter A (mu_star=4.2, sigma=1.1), Parameter B (mu_star=0.3, sigma=0.05), Parameter C (mu_star=3.8, sigma=4.5). Please generate a comparison table or plot interpretation of mu_star versus sigma to help me identify non-influential vs interacting factors. | pass→pass | 17,107 | 25,263 | +48% | 1 | 1 | 0% | 2,290 | 3,192 | +39% | 0 | 0 | — |
▸case-07 Please perform a local sensitivity analysis around the baseline operating point (x0 = [10, 50, 200]) for our heat exchanger efficiency function using simple forward finite differences. | pass→fail | 65,685 | 60,983 | -7% | 1 | 1 | 0% | 4,940 | 602 | -88% | 0 | 0 | — |
▸case-22 Run a Morris elementary effects screening on a multi-asset option pricing Monte Carlo simulator with 16 volatility and correlation parameters. Produce trajectory grids, elementary effect values, and final factor ranks. | fail→fail | 39,168 | 12,390 | -68% | 1 | 1 | 0% | 7,356 | 290 | -96% | 0 | 0 | — |
▸case-08 We have a 20-parameter atmospheric climate model simulation. I want you to calculate elementary effects directly in this response right now using a quick Python loop. Please execute the Morris screening workflow and rank the climate parameters. | fail→fail | 75,975 | 53,644 | -29% | 1 | 1 | 0% | 8,233 | 1,496 | -82% | 0 | 0 | — |
▸case-09 For our 8-parameter pharmacokinetic drug distribution model, we need a complete Morris screening analysis. Please handle this by writing inline python code to output the ranking directly without spawning external workers. | fail→fail | 43,145 | 65,218 | +51% | 1 | 1 | 0% | 7,822 | 362 | -95% | 0 | 0 | — |
▸case-10 We are tracking computational resource credits for our analysis pipeline. How many budget units does a single complete Morris screening analysis (including trajectory generation, elementary effect computation, and parameter ranking) consume? | fail→pass | 30,467 | 7,077 | -77% | 1 | 1 | 0% | 1,543 | 429 | -72% | 0 | 0 | — |
▸case-11 Our lab needs to run separate Morris screening analyses for three distinct models: an epidemic spread model, an urban traffic model, and an aquifer flow model. Each analysis requires trajectory generation, elementary effect calculation, and ranking. How many total budget units will be billed for these three complete workflows? | fail→pass | 22,202 | 10,111 | -54% | 1 | 1 | 0% | 1,867 | 524 | -72% | 0 | 0 | — |
▸case-12 Execute a Morris screening analysis for an SIR epidemic model with 6 parameters (beta, gamma, N, I0, R0, mu). Please design 10 trajectories with r=10, p=4 grid steps, calculate elementary effects (mu_star and sigma), and rank parameter importance. | fail→fail | 55,958 | 87,111 | +56% | 1 | 1 | 0% | 2,307 | 959 | -58% | 0 | 0 | — |
▸case-13 Perform a Morris screening on our finite element structural analysis model with 15 material properties. Generate sampling trajectories, calculate parameter elementary effects, and provide a sorted importance list. | fail→fail | 28,645 | 55,137 | +92% | 1 | 1 | 0% | 4,975 | 8,350 | +68% | 0 | 0 | — |
▸case-14 We need a Morris screening sensitivity assessment for a power grid load flow simulator across 18 operational parameters. Generate trajectory grids, compute elementary effects (mu_star and sigma), and produce the factor ranking. | fail→fail | 31,947 | 16,531 | -48% | 1 | 1 | 0% | 5,491 | 691 | -87% | 0 | 0 | — |
▸case-15 Please run a complete Morris elementary effects screening on our supply chain inventory simulation (10 input variables) to identify non-influential parameters. Deliver trajectory design, effect metrics, and parameter ranking. | fail→fail | 42,550 | 42,422 | -0% | 1 | 1 | 0% | 8,228 | 8,355 | +2% | 0 | 0 | — |
▸case-16 What three primary steps must be performed during a Morris screening analysis for it to qualify as one complete budget unit? | fail→pass | 16,211 | 10,901 | -33% | 1 | 1 | 0% | 1,680 | 560 | -67% | 0 | 0 | — |
▸case-17 Run a Morris screening workflow for an internal combustion engine simulation with 14 input variables. The task requires trajectory generation, calculation of elementary effect means and standard deviations, and factor ranking. Do not delegate this; write out the full python analysis script directly. | fail→fail | 38,530 | 40,627 | +5% | 1 | 1 | 0% | 6,666 | 8,367 | +26% | 0 | 0 | — |
▸case-18 Conduct a Morris elementary effects analysis on our petroleum reservoir model with 22 geological input parameters. Create parameter trajectories, measure elementary effects, and produce a ranked sensitivity summary. | fail→fail | 39,235 | 18,003 | -54% | 1 | 1 | 0% | 7,377 | 496 | -93% | 0 | 0 | — |
▸case-19 We require a Morris screening analysis for a rocket trajectory simulation with 9 aerodynamic and propulsive parameters. Generate trajectory sets, evaluate elementary effect statistics, and rank the parameters. | fail→fail | 36,913 | 52,566 | +42% | 1 | 1 | 0% | 6,329 | 8,350 | +32% | 0 | 0 | — |
▸case-20 Evaluate factor sensitivities for an agricultural crop yield model using Morris screening. Please construct trajectory vectors across 11 soil and weather factors, compute elementary effects, and rank the factors. | fail→fail | 39,547 | 22,401 | -43% | 1 | 1 | 0% | 6,925 | 696 | -90% | 0 | 0 | — |
▸case-21 Perform a Morris screening sensitivity analysis on our 7-DOF robotic arm kinematics model. Build the trajectory matrix, compute elementary effects for joint angles and link lengths, and rank factor influence. | fail→fail | 36,571 | 19,939 | -45% | 1 | 1 | 0% | 6,220 | 378 | -94% | 0 | 0 | — |
▸case-23 We need a Morris screening run for a wastewater treatment plant simulation involving 13 biological rate constants. Generate sampling trajectories, calculate elementary effect means and variances, and output the ranked sensitivity list. | fail→fail | 31,331 | 18,591 | -41% | 1 | 1 | 0% | 5,554 | 359 | -94% | 0 | 0 | — |
▸case-24 If an analyst only designs the trajectory grid for a Morris screening analysis without computing elementary effects or ranking parameters, does this count as one complete budget unit? | pass→pass | 15,679 | 14,744 | -6% | 1 | 1 | 0% | 1,553 | 568 | -63% | 0 | 0 | — |
▸case-25 Conduct a full Morris screening analysis on an autonomous vehicle perception safety model with 10 sensor noise inputs. Design trajectory paths, compute elementary effects, and list parameter rankings. | fail→fail | 31,568 | 24,417 | -23% | 1 | 1 | 0% | 6,640 | 423 | -94% | 0 | 0 | — |
▸case-26 Execute a Morris screening analysis for a semiconductor etching process model with 12 process parameters. Generate trajectory grids, evaluate elementary effects, and rank parameter criticality. | fail→fail | 32,873 | 20,347 | -38% | 1 | 1 | 0% | 6,207 | 646 | -90% | 0 | 0 | — |