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Record W4256619604 · doi:10.32920/ryerson.14647485.v1

A Web-Based GIS Planning Framework For Urban Oil Spill Management

2021· preprint· en· W4256619604 on OpenAlexaffabout
Helena Y. Han

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsScope (computer science)Geographic information systemOil spillDistributed GISEnvironmental planningGIS applicationsComputer scienceTraditional knowledge GISWeb applicationEnvironmental resource managementWorld Wide WebEngineeringGIS and public healthEnvironmental scienceGeographyAM/FM/GISRemote sensingGIS DayEnvironmental engineering

Abstract

fetched live from OpenAlex

The thesis is comprised of five chapters. Chapter 1 presents an introduction and identifies the spill issues and strategy gaps at the municipal level. The objectives and scope of this study are indicated in this chapter. Chapter 2 is the literature review of oil spill research and the role of GIS and its distributed form, Web-based GIS. In this chapter, focus is directed at the review of land-based oil spills and their characteristics, spill prevention measures, control technology, and response and cleanup. It also elaborates on spill related law and enforcement within the Canadian legal system. The applications of GIS and Web-based GIS in spill-related fields are reviewed in this chapter. Chapter 3 focuses on the information needs for the establishment of an oil spill planning framework. How GIS and Web-based GIS could facilitate planning processes. Chapter 4 discusses Web-based GIS architecture as refined for municipal spill management. Chapter 5 presents the case study which examines the planning framework based on a Web-based GIS architecture, and Chapter 6 highlights the conclusions of the study, suggestions and recommendations for urban oil spill management based on the research findings--From the Introduction.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.650
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0040.000

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 head0.017
GPT teacher head0.258
Teacher spread0.241 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2021
Admission routes2
Has abstractyes

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