.. Auto-generated by scripts/generate_problem_catalog_docs.py. Do not edit by hand.

Decision Problem - MSEval Safety Helmet (Lightweight)
=====================================================

Choose one material for Safety Helmet with emphasis on Lightweight, using expert MSEval survey responses as the evaluation benchmark.

See :doc:`../decision` for the decision family index.

Quick Facts
-----------

.. list-table::
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   * - Field
     - Value
   * - Problem ID
     - ``decision_mseval_safety_helmet_lightweight``
   * - Problem Family
     - decision
   * - Implementation
     - ``design_research_problems.problems.decision._mseval:MSEvalEmpiricalChoiceProblem``
   * - Capabilities
     - ``citation-backed``, ``statement-markdown``
   * - Study Suitability
     - none
   * - Tags
     - ``decision``, ``material-selection``, ``mseval``, ``safety_helmet``, ``lightweight``

Taxonomy
--------

Formulation
   empirical_discrete_choice
Design Variable Type
   categorical
Is Dynamic
   no
Orientation
   engineering_practical
Objective Mode
   single
Constraint Nature
   preference-derived
Tags
   ``decision``, ``material-selection``, ``mseval``, ``safety_helmet``, ``lightweight``

Statement
---------

.. code-block:: markdown

   # Decision Problem - MSEval Safety Helmet (Lightweight)

   You are selecting a material for **Safety Helmet**.

   Primary criterion: **Lightweight**.

   ## Task
   1. Choose **one** material from the list below.
   2. Briefly justify the choice in terms of the stated criterion and likely use context.
   3. Optionally note one follow-up risk or tradeoff to validate next.

   ## Candidate Materials
   - Steel
   - Aluminium
   - Titanium
   - Glass
   - Wood
   - Thermoplastic
   - Elastomer
   - Thermoset
   - Composite

   ## Output Format
   - Selected material:
   - Justification (3-6 sentences):
   - Risk or tradeoff to check next (optional):

Decision Context
----------------

.. list-table::
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   * - Field
     - Value
   * - Decision Maker
     - A designer selecting one material conceptually for a safety helmet.
   * - Market Segment
     - MSEval expert benchmark with 67 complete responses for this prompt.
   * - Decision Scope
     - Choose a single candidate material from the provided materials using an empirical preference benchmark derived from MSEval survey responses.

Objectives
----------

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   * - Key
     - Label
     - Sense
     - Domain
     - Executable
     - Variables
     - Expression
   * - expert_agreement
     - Tie-adjusted expert top-choice share
     - maximize
     - empirical-choice
     - yes
     - ``material``
     - sum_i I(choice in argmax_i)/\|argmax_i\| / N

Candidate Space
---------------

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   * - Field
     - Value
   * - Candidate Kind
     - empirical-choice
   * - Candidate Count
     - 9
   * - Default Choice Metric
     - top-choice-share
   * - Response Count
     - 67

Empirical Benchmarks
~~~~~~~~~~~~~~~~~~~~

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   :widths: 14 30 14 14 14 14

   * - Key
     - Label
     - Top Choice Share
     - Mean Rating
     - Median Rating
     - Std Rating
   * - steel
     - Steel
     - 0.001658
     - 2.20896
     - 2
     - 2.18492
   * - aluminium
     - Aluminium
     - 0.091211
     - 5.23881
     - 5
     - 3.15311
   * - titanium
     - Titanium
     - 0.111111
     - 5.28358
     - 7
     - 3.302
   * - glass
     - Glass
     - 0.016584
     - 1.1194
     - 1
     - 1.52278
   * - wood
     - Wood
     - 0.00539
     - 2.71642
     - 2
     - 2.37924
   * - thermoplastic
     - Thermoplastic
     - 0.178275
     - 6.0597
     - 6
     - 2.88087
   * - elastomer
     - Elastomer
     - 0.024046
     - 4.46269
     - 4
     - 2.72657
   * - thermoset
     - Thermoset
     - 0.019071
     - 4.67164
     - 5
     - 2.65939
   * - composite
     - Composite
     - 0.552653
     - 8.50746
     - 9
     - 2.04771

Sources
-------

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   * - Key
     - Summary
   * - ``jain2024msevaldatasetmaterialselection``
     - Yash Patawari Jain, Daniele Grandi, Allin Groom, Brandon Cramer, Christopher McComb (2024). MSEval: A Dataset for Material Selection in Conceptual Design to Evaluate Algorithmic Models

Raw Citation Records
--------------------

.. code-block:: bibtex

   @misc{jain2024msevaldatasetmaterialselection,
         title={MSEval: A Dataset for Material Selection in Conceptual Design to Evaluate Algorithmic Models},
         author={Yash Patawari Jain and Daniele Grandi and Allin Groom and Brandon Cramer and Christopher McComb},
         year={2024},
         eprint={2407.09719},
         archivePrefix={arXiv},
         primaryClass={cs.LG},
         url={https://arxiv.org/abs/2407.09719},
   }