MétaCan
Menu
Back to cohort
Record W1944831574 · doi:10.15353/pced.v11i0.13

Municipal GIS in Northern Ontario status and strategies

2014· article· en· W1944831574 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePapers in Canadian Economic Development · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsInnovation, Science and Economic Development Canada
Fundersnot available
KeywordsZoningGeographic information systemSoftware deploymentGIS applicationsEnvironmental planningGIS DayGeographyEnvironmental resource managementGIS file formatKey (lock)GIS and public healthAM/FM/GISComputer scienceRemote sensingCivil engineeringEngineeringEnvironmental scienceComputer security

Abstract

fetched live from OpenAlex

Geographic Information Systems (GIS) are an important tool for economic developers to capture, manipulate and interpret local data from a myriad of sources including municipal infrastructure data, land assets, local zoning by-laws, building codes, local maps and aerial photographs. This paper provides a description of GIS technologies and applications; reviews the status of municipal GIS across Northern Ontario and; presents key success elements that should be considered by municipal governments and their staff when developing GIS strategies and networks. The elements will increase the likelihood of a successful deployment and the long-term viability of the GIS solution.Keywords: Geographic Information Systems (GIS), Northern Ontario, municipal governments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.225
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it