Defend a conditional site alternative without hiding constraints in a score
An environmental decision requires more than choosing the largest resource estimate or the smallest average hazard. The decision-maker must state which outcomes are constraints, which can be compared, which scenarios are credible and whose impacts remain unrepresented. A numerical ranking cannot silently decide those ethical and practical boundaries.
Learning outcome: Compare dry-only and both-scenario screening at each cap. Retain the rejected as well as selected alternatives and the exact decision rule. Identify a nonmonetized outcome and one uncertainty that the displayed cost ranking does not resolve.
Starting recap
Retain resource inventories, physical force and reaction boundaries, chronological alternatives and explicit decision constraints. Conditional teaching results do not certify actual site suitability.
All lessons are open directly. Your saved experiments remain when you leave and return.
Try
With cap 6 and both scenarios, A fails because wet load is 9; B and C pass with worst loads 6 and 4. B is least cost among feasible options at 12. Under dry-only screening A would pass at cost 8, illustrating why the scenario requirement matters.
Open the experimentPredict
Can an option that is cheapest and feasible in one scenario fail a requirement applied across two scenarios?
Experiment
Compare dry-only and both-scenario screening at each cap. Retain the rejected as well as selected alternatives and the exact decision rule. Identify a nonmonetized outcome and one uncertainty that the displayed cost ranking does not resolve.
Screen alternatives under explicit environmental constraints
Worked teaching model · synthetic values · Original options: A cost 8, dry/wet loads 3/9; B cost 12, loads 4/6; C cost 15, loads 2/4. Screen against the user-selected teaching cap, then minimize stipulated cost among feasible options. These are invented constraints, not legal limits, monetized ecological values or an actual site recommendation.
Reset keeps your prediction, captures and practice history.
An explicit environmental constraint is not interchangeable with a hidden weighted score.
The model picks the cheapest option only after checking the selected scenarios and teaching cap. Wet-weather performance, uncertainty, protected values and who bears residual impacts need separate review. All inputs and the cap are invented, not a legal standard or site approval.
Option A: Cost 8, dry load 3, wet load 9, screened load 9, exceeds cap
Option B: Cost 12, dry load 4, wet load 6, screened load 6, within cap
Option C: Cost 15, dry load 2, wet load 4, screened load 4, within cap
| Quantity | Value | Unit |
|---|---|---|
| Option A meets chosen constraint | 0 | 0 no / 1 yes |
| Option B meets chosen constraint | 1 | 0 no / 1 yes |
| Option C meets chosen constraint | 1 | 0 no / 1 yes |
| Feasible option count | 2 | count |
| Least-cost feasible option index | 1 | A=0 / B=1 / C=2 |
| Least feasible stipulated cost | 12 | fictional cost units |
Original instructional packets and diagrams, not actual site measurements, legal limits or professional clearance.
An explicit environmental constraint is not interchangeable with a hidden weighted score.
The model picks the cheapest option only after checking the selected scenarios and teaching cap. Wet-weather performance, uncertainty, protected values and who bears residual impacts need separate review. All inputs and the cap are invented, not a legal standard or site approval.
Captures preserve recipes and replay their calculated results. They are synthetic model evidence, not physical measurements.
Understand
Apply
Public practice checks a specific claim. It does not establish independent mastery.
With cap 4 and both scenarios, which option qualifies? What changes if only the dry scenario is screened?
Continue
Completion requires a saved prediction, at least one capture and a reflection. Presence checks do not grade your reasoning.
Skipping retains experiments and awards no mastery.
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