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Record W2981502829 · doi:10.4095/299757

Ottawa harvested hydrogeological information geodatabase

2017· report· en· W2981502829 on OpenAlexaboutno aff
M. Below, Caroline Michel, Michael W. Kearney, C Milloy

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSpatial databaseHydrogeologyGeographyDatabaseCartographyComputer scienceSpatial analysisRemote sensingGeology

Abstract

fetched live from OpenAlex

Several of the conservation authorities (CA) in eastern Ontario are partnered with the City of Ottawa to provide technical advice about hydrogeological studies that are submitted to the City in support of development applications and about related policy and guidance development. These CA's also facilitate Source Protection initiatives for the local Source Protection Regions and maintain an ongoing partnership with the Ministry of the Environment and Climate Change (MOECC) to collect data from local Provincial Groundwater Monitoring Network (PGMN) wells. In addition, the City also owns information from municipal wells and data from numerous land use monitoring programs. As a result of the above responsibilities, the CAs and City house a tremendous amount of hydrogeological information in separate paper, pdf, tabular, and various old database formats; all of which has never been catalogued. Moreover, this data cannot currently be accessed, summarized, mapped or analysed together. However, there are on-going demands for the presentation and use of this information during the course of regular municipal and conservation authority business. To address the above hydrogeological data management gap, in 2016, the City of Ottawa in partnership with the Rideau Valley Conservation Authority implemented a project to develop a hydrogeological geodatabase and data harvesting plan. This presentation will provide an overview of the project context, outcomes and anticipated next-steps.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0170.006

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 head0.053
GPT teacher head0.266
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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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