AI initiative registry

Every initiative listed in the registry can be consulted here, without an account. Each record shows its progress, its milestones and the history of its decisions. Requests still under triage do not appear: they join the registry once reviewed.

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63 initiative(s)

AI initiative registry
ID	AI Initiative	Current Status	Description	Sector	Region	AI Bucket	SME
140	Clustering to characterize extreme marine conditions for the benthic region of the Northeastern Pacific continental margin	Pilot	We introduce a method for characterizing extremes that uses machine learning to divide the data into regions with relatively consistent envi...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
137	Method Recommendation Engine	Pilot	A large language model reviews a scientist’s objective for collecting data in the field and based on the criteria, the model will provide th...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
135	PII & Sensitivity Scores	Pilot	Determines the sensitivity of the content of a document based on a trained model and allows for the redaction of the sensitive material in t...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
133	LLM Document Extraction - Prompt Engineering to Retrieve Relevant Information	Pilot	Using LLM to extract key information from documents with multiple templates using prompt engineering approaches. These results are reviewed...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
128	CICADA (cumulative effects spatial data tool) Phase 2: determining stressor effects and interactions to inform decision-making	Pilot	Geospatial and machine learning techniques will be applied to determine the overall effect, stress(or) interactions, and relative influences...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
127	Automated assessment of Crowd Source Bathymetry	Pilot	The Community Hydrography team is working with the University of New Brunswick (UNB) on a tool-kit that will automate the assessment of larg...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
125	Automated Paper Chart Solution	Pilot	CHS is working closely with software provider CARIS to test and implement automated solution to generate Paper Charts from digital data sour...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
121	Develop a deep-learning model to age capelin otoliths: application for stock assessment	Pilot	Investigate the utility of applying a deep-learning model developed by the DFO Gulf Region for aging fish otoliths; specifically, to determi...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
120	Characterizing areas of convergence in the Saint John Harbour	Pilot	This project is using a technique called self-organizing maps, which is an unsupervised machine learning algorithm, to identify patterns in...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
117	PolyDocs: Format and Translate for CSAS	Production	A modular, bilingually-optimized (EN/FR) application that automates the formatting, quality assurance, and standardization of complex Word d...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Carr, Kevin
116	BinderBot: A Smart Planning Binder	Pilot	Employs AI-driven extraction to identify and compile the most relevant data from technical documents for the planning binder. Streamlines t...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
113	Improving forecasting for high-priority ports	Pilot	Research into feasibility of improving accuracy and timeliness of short-term forecasts for coastal regions by combining traditional and AI m...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
108	The development of rapid multiplex qPCR for the detection and quantification of three parasites MSX, SSO, Dermo of oysters (Crassostrea virginica) and MSX single-cell whole genome sequencing using long read sequencing platform’	Pilot	This 2-year project aims to enhance the disease diagnostic services provided to the shellfish aquaculture industry by improving the methods...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
99	Improved freshwater runoff modelling in Eastern Canada to drive ocean models	Pilot	Use Neural Networks to post-process streamflow simulations from the WRF-Hydro model, improving their agreement with observational data. Thes...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
98	Guidance on Optimal Timing for Environmental DNA (GOTeDNA)	Pilot	Provide guidance on optimal eDNA sampling periods and standardized sampling procedures for assessing and monitoring coastal species using eD...	Ecosystems and Oceans Science	National Capital Region	Automation and Decision Support	Winegardner, Amanda
83	Daily Use	Pilot	Mapping, The AI Assist function in FME has been used to support code development for data processing while integrating and manipulating data...	Programs Sector	National Capital Region	Automation and Decision Support	Newman, Candace
75	Study on the use of Artificial Neural Networks to Predict the Return Timing and Northern Diversion Rate for Migrating Fraser River Sockeye Salmon	Idea	The Machine Learning feasibility study compliments the statistical approach by asking whether Artificial Intelligence (AI) methods can be de...	Ecosystems and Oceans Science	Pacific	Automation and Decision Support	Thomson, Richard
70	Data Validation Tool (See B6, B22)	Pilot	Use large language models to help detect errors in data transcribed using optical character recognition. Apply validation rules to propose...	Ecosystems and Oceans Science	Pacific	Automation and Decision Support	Bird, Tom
69	Species distribution modeling	Pilot	Species distribution models for various coral/sponge/groundfish Random Forests	Ecosystems and Oceans Science	Pacific	Automation and Decision Support	Rooper, Chris
67	Nearshore biotopes model	Idea	model to define and map nearshore biotope was developed and presented at CSAS Mar 3-4, 2025 - the paper was accepted with revisions but not...	Ecosystems and Oceans Science	Pacific	Automation and Decision Support	Lessard, Joanne
65	Comprehensive marine substrate classification applied to Canada’s Pacific shelf	Pilot	We built five regional and one coastwide substrate model for the BC coast using substrate observations and seafloor bathymetry derivatives a...	Ecosystems and Oceans Science	Pacific	Automation and Decision Support	Haggarty, Dana
61	CTD data QC using ML	Pilot	Working with CDOS office to streamline our CTD QC using ML cnn and others	Ecosystems and Oceans Science	Pacific	Automation and Decision Support	Guan, Lu
59	Clustering to characterize extreme marine conditions for the benthic region of the Northeastern Pacific continental margin	Pilot	We introduce a method for characterizing extremes that uses machine learning to divide the data into regions with relatively consistent envi...	Ecosystems and Oceans Science	Pacific	Automation and Decision Support	Holdsworth, Amber
56	Method Recommendation Engine	Idea	A large language model reviews a scientist’s objective for collecting data in the field and based on the criteria, the model will provide th...	Programs Sector	Pacific	Automation and Decision Support	Quan, Eric
54	PII & Sensitivity Scores	On hold On hold	Determines the sensitivity of the content of a document based on a trained model and allows for the redaction of the sensitive material in t...	Programs Sector	Pacific	Automation and Decision Support	Quan, Eric

140
Clustering to characterize extreme marine conditions for the benthic region of the Northeastern Pacific continental margin
We introduce a method for characterizing extremes that uses machine learning to divide the data into regions with relatively consistent environmental conditions (temperature, oxygen, acidity), and define the extremes based on the historical statistics of variability of each of these fields.

Pilot Ecosystems and Oceans Science Automation and Decision Support
137
Method Recommendation Engine
A large language model reviews a scientist’s objective for collecting data in the field and based on the criteria, the model will provide the best procedure to use for their work

Pilot Ecosystems and Oceans Science Automation and Decision Support
135
PII & Sensitivity Scores
Determines the sensitivity of the content of a document based on a trained model and allows for the redaction of the sensitive material in the document.

Pilot Ecosystems and Oceans Science Automation and Decision Support
133
LLM Document Extraction - Prompt Engineering to Retrieve Relevant Information
Using LLM to extract key information from documents with multiple templates using prompt engineering approaches. These results are reviewed by SMEs to ensure accuracy and relevancy.

Pilot Ecosystems and Oceans Science Automation and Decision Support
128
CICADA (cumulative effects spatial data tool) Phase 2: determining stressor effects and interactions to inform decision-making
Geospatial and machine learning techniques will be applied to determine the overall effect, stress(or) interactions, and relative influences of different stresses(ors) on fish metrics such as species occupancy, population status or community status.

Pilot Ecosystems and Oceans Science Automation and Decision Support
127
Automated assessment of Crowd Source Bathymetry
The Community Hydrography team is working with the University of New Brunswick (UNB) on a tool-kit that will automate the assessment of large volumes of crowd source data. AI routines will allow for automated QC, and drafting of Navigation Warnings.

Pilot Ecosystems and Oceans Science Automation and Decision Support
125
Automated Paper Chart Solution
CHS is working closely with software provider CARIS to test and implement automated solution to generate Paper Charts from digital data sources. AI routines will improve speed and accuracy of solutions (machine learning) as software is refined to ensure product specifications are respected (as they are used for official navigation).

Pilot Ecosystems and Oceans Science Automation and Decision Support
121
Develop a deep-learning model to age capelin otoliths: application for stock assessment
Investigate the utility of applying a deep-learning model developed by the DFO Gulf Region for aging fish otoliths; specifically, to determine the age of capelin in the 2J3KL stock in Newfoundland for use in stock assessments. Otolith aging is currently done visually using a microscope, this proposed method would automate that process to save time and resources, while reducing human error and bias

Pilot Ecosystems and Oceans Science Automation and Decision Support
120
Characterizing areas of convergence in the Saint John Harbour
This project is using a technique called self-organizing maps, which is an unsupervised machine learning algorithm, to identify patterns in areas of convergence near the Saint John Harbour. The preliminary analysis suggests that these patterns are related to different environmental conditions such as river discharge and tidal phase. The work has been conducted in collaboration with scientists from the Maritimes Region and is currently on hold.

Pilot Ecosystems and Oceans Science Automation and Decision Support
117
PolyDocs: Format and Translate for CSAS
A modular, bilingually-optimized (EN/FR) application that automates the formatting, quality assurance, and standardization of complex Word documents to meet Government of Canada publishing requirements. The tool orchestrates a highly configurable, low-code assembly line that handles deep document cleanup (resolving fragmented text, localizing punctuation/number conventions, and rebuilding tables of contents), applies localized terminology glossaries, and reduces file sizes for accessibility.

Production Ecosystems and Oceans Science Automation and Decision Support
116
BinderBot: A Smart Planning Binder
Employs AI-driven extraction to identify and compile the most relevant data from technical documents for the planning binder. Streamlines the planning binder process by automatically assembling targeted, information ready for executive review. Saves valuable administrative time and ensures that binder materials are both comprehensive and user-friendly.

Pilot Ecosystems and Oceans Science Automation and Decision Support
113
Improving forecasting for high-priority ports
Research into feasibility of improving accuracy and timeliness of short-term forecasts for coastal regions by combining traditional and AI modelling methods.

Pilot Ecosystems and Oceans Science Automation and Decision Support
108
The development of rapid multiplex qPCR for the detection and quantification of three parasites MSX, SSO, Dermo of oysters (Crassostrea virginica) and MSX single-cell whole genome sequencing using long read sequencing platform’
This 2-year project aims to enhance the disease diagnostic services provided to the shellfish aquaculture industry by improving the methods for detecting economically important Oyster parasites, enhance understanding of Multinucleate Sphere Unknown X (MSX) virulence dynamics, and support the creation of new vaccine in investigating future outbreaks and modeling through machine learning.

Pilot Ecosystems and Oceans Science Automation and Decision Support
99
Improved freshwater runoff modelling in Eastern Canada to drive ocean models
Use Neural Networks to post-process streamflow simulations from the WRF-Hydro model, improving their agreement with observational data. These neural networks are applied as a downstream calibration step. Builds synergy between traditional calibration methods and modern AI techniques in hydrologic modeling.

Pilot Ecosystems and Oceans Science Automation and Decision Support
98
Guidance on Optimal Timing for Environmental DNA (GOTeDNA)
Provide guidance on optimal eDNA sampling periods and standardized sampling procedures for assessing and monitoring coastal species using eDNA. GOTeDNA, a centralized interactive online tool currently in development, will report/visualize trends in spatio-temporal eDNA distributions.

Pilot Ecosystems and Oceans Science Automation and Decision Support
83
Daily Use
Mapping, The AI Assist function in FME has been used to support code development for data processing while integrating and manipulating data in workbenches.

Pilot Programs Sector Automation and Decision Support
75
Study on the use of Artificial Neural Networks to Predict the Return Timing and Northern Diversion Rate for Migrating Fraser River Sockeye Salmon
The Machine Learning feasibility study compliments the statistical approach by asking whether Artificial Intelligence (AI) methods can be developed to predict salmon behaviour as functions of ocean conditions. classical machine learning models, including linear regression, Ridge regression, and Random Forest

Idea Ecosystems and Oceans Science Automation and Decision Support
70
Data Validation Tool (See B6, B22)
Use large language models to help detect errors in data transcribed using optical character recognition. Apply validation rules to propose corrections and normalize data into a standardized format. (Digitizing non-machine-readable (handwritten) documents and extracts characters into a digital format) Llama 3.0 Large Language Model

Pilot Ecosystems and Oceans Science Automation and Decision Support
69
Species distribution modeling
Species distribution models for various coral/sponge/groundfish Random Forests

Pilot Ecosystems and Oceans Science Automation and Decision Support
67
Nearshore biotopes model
model to define and map nearshore biotope was developed and presented at CSAS Mar 3-4, 2025 - the paper was accepted with revisions but not to the methods. The model use sdmTMB to predict species and then use k-means clustering method to find species assemblages. Large datasets can be used. R scripts for sdmTMB, k-means cluster, figures

Idea Ecosystems and Oceans Science Automation and Decision Support
65
Comprehensive marine substrate classification applied to Canada’s Pacific shelf
We built five regional and one coastwide substrate model for the BC coast using substrate observations and seafloor bathymetry derivatives and oceanographic predictors using Random Forests. Random Forests

Pilot Ecosystems and Oceans Science Automation and Decision Support
61
CTD data QC using ML
Working with CDOS office to streamline our CTD QC using ML cnn and others

Pilot Ecosystems and Oceans Science Automation and Decision Support
59
Clustering to characterize extreme marine conditions for the benthic region of the Northeastern Pacific continental margin
We introduce a method for characterizing extremes that uses machine learning to divide the data into regions with relatively consistent environmental conditions (temperature, oxygen, acidity), and define the extremes based on the historical statistics of variability of each of these fields. unsupervised clustering with k-means

Pilot Ecosystems and Oceans Science Automation and Decision Support
56
Method Recommendation Engine
A large language model reviews a scientist’s objective for collecting data in the field and based on the criteria, the model will provide the best procedure to use for their work

Idea Programs Sector Automation and Decision Support
54
PII & Sensitivity Scores
Determines the sensitivity of the content of a document based on a trained model and allows for the redaction of the sensitive material in the document. Presidio

On hold On hold Programs Sector Automation and Decision Support