Tephra classification with machine learning [2024 INV#WO0000000109095]

Overview

Development stage

PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Not reported

Start date

2023-01-01 (day precision)Source: 1/1/2023

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Science

Operational functions

No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Layers of volcanic ash can be classified using a their geochemical components to link a the ash to the volcano it erupted from.

Expected benefits

This model helps probabilistically identify distal tephra layers from throughout the region, helping us better understand its long-term record of explosive volcanism.

System outputs

Identification of the source volcano of tephra layers in the form of prediction sets and probabilities eg {Katmai: .82, Augustine: 0.15, Redoubt: .03}

Technology

AI classification

Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…

System name(s)

Not reported

Custom-developed code

No

Public source code

Not reported

Sourcing

How it was built

Developed in-houseSource: b) Developed in-house

Vendor (as reported)

Not reported

Vendors (standardized)

None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

No

Privacy Impact Assessment

Not reported

Authorization to Operate

Yes

Demographic features

k) None of the above

Training and evaluation data

Data associated with this data release: https://dggs.alaska.gov/pubs/id/31091

Federal Data Catalog

dggs.alaska.gov ↗

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported