Methodology
How Periodic Engine
scores strategic
elements.
Periodic Engine uses modeled intelligence scores to evaluate element-level importance, supply-chain exposure, substitution difficulty, and future technology relevance across critical industries.
Modeled scores. Source-backed methodology. Reviewed intelligence. Explainable assumptions.
5
Scoring Dimensions
12
Genesis 12 Active
3
Confidence Levels
Reviewed Dates
Last reviewed markers
Source Context
Public source categories
From static element data to strategic intelligence.
Periodic Engine does more than collect public data. We normalize, connect, interpret, and score public source categories to produce decision-support context for every element.
Source Context
We draw from authoritative public sources, research, and documented assumptions across multiple source categories.
Dependency Mapping
We map how each element supports critical industries, systems, and future technologies.
Modeled Scorecard
We score five dimensions, assign confidence, and explain the story behind the scores.
The five scoring dimensions.
Each dimension is scored from 0–100 and contributes to the overall modeled score.
1. Civilization Impact
Measures how essential an element is to modern infrastructure, industrial systems, energy, communications, health, computing, transportation, and defense.
Signals considered
2. Supply-Chain Risk
Measures exposure to concentration, import reliance, by-product dependency, export sensitivity, recycling limitations, and fragile supply routes.
Signals considered
3. Strategic Value
Measures an element's importance to national security, advanced manufacturing, AI infrastructure, semiconductors, defense, aerospace, telecom, and energy.
Signals considered
4. Substitution Difficulty
Measures how hard it is to replace an element in key applications without performance loss, cost increases, redesign burden, or supply-chain disruption.
Signals considered
5. Future Technology Relevance
Measures expected relevance to future technology stacks: AI infrastructure, power electronics, grid modernization, advanced mobility, space systems, quantum systems, and next-generation defense platforms.
Signals considered
How to read a scorecard.
Example: Gallium (Ga)
Ga
Gallium
Overall Modeled Score
Dimension Scores (0–100)
Scorecard Fields
Overall Modeled Score
Weighted combination of five dimensions.
Confidence Level
How strongly source context supports the scores.
Reviewed Date
When this element profile was last reviewed.
Source Context
Public source categories behind the profile.
Key Takeaway
Core insight that explains the score.
Supply Context
How and where the element is produced.
Connected Elements
Related elements that influence the story.
Substitution Notes
Key notes on replacement difficulty.
What each field means
Overall score
Weighted combination of five dimensions
Dimension scores
0–100 per dimension
Confidence level
How strong the source context is
Reviewed date
Last modeled review
Source context
Public source categories used
Key takeaway
Executive summary
Supply context
Concentration, imports, by-product, recycling
Connected elements
Key material links
Substitution notes
Replacement difficulty
Trust signals inside every scorecard.
These signals help you interpret the strength and currency of each score.
Confidence Levels
Reflect how strongly the available source context and model assumptions support the score.
Reviewed Dates
Show when an element profile was last reviewed. Reviewed dates are trust markers, not automatic update claims.
Source Context
Indicates the public source categories used to build the profile. See all source categories on the Sources page.
What the scores are and are not.
Scores are
Scores are not
Periodic Engine scores are modeled intelligence signals. They are not credit ratings, analyst ratings, financial advice, procurement instructions, or guarantees of disruption.
Why Genesis 12 comes first.
Genesis 12 is the initial strategic element set used to validate the scoring model, page structure, supply context maps, and element intelligence workflow before expanding to the full periodic table.
The remaining elements are visible in the Engine and database. They are not fully modeled in this release.
Our modeling workflow.
A repeatable process for building every element profile.
Source category review
Collect and assess public sources.
Industry dependency mapping
Map critical industries and systems.
Supply-chain exposure assessment
Evaluate concentration, imports, by-product supply, recycling, and export risk.
Substitution & future relevance analysis
Assess substitution difficulty and future technology alignment.
Modeled scorecard review
See all source context, assign confidence, and set reviewed date.
Model assumptions may be refined as new source context becomes available.
Explore the model in action.
Open the Engine, review element profiles, or explore the Genesis 12 database to see this methodology across real scorecards.