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Record W2981932227 · doi:10.4095/297734

Conservation authority geoscience programs

2016· report· en· W2981932227 on OpenAlexaboutno aff
Michael Millar

Bibliographic record

Venuenot available
Typereport
Languageen
FieldSocial Sciences
TopicArchaeology and Natural History
Canadian institutionsnot available
Fundersnot available
KeywordsEarth scienceEnvironmental scienceGeographyEnvironmental resource managementGeology

Abstract

fetched live from OpenAlex

Geoscience is a relatively new program area for many Conservation Authorities (CA); it wasn't until about 2001 that CAs started to employ Geoscientists. Initial CA geoscience programs consisted of the newly formed Provincial Groundwater Monitoring Network (PGMN) and the Source Water Protection (SWP) Program. The Geoscience services offered by CAs has evolved and is now more integrated into regular CA business and has opened up additional opportunities for collaborations with municipal, provincial, and federal partners. In 2008 the CA Geosciences Group was formed to ensure consistency between CAs for the application of geoscience among CAs. Of the 36 CAs approximately 14 CAs currently employ qualified geoscientists, the remaining 22 contract out geosciences work as required. This presentation will look at how geoscience has been integrated into the core CA business, which includes 1. Aspects of planning and development review; review and commenting on public policy and regulations; 2. Watershed Plans, including the watershed Report Cards; 3. Monitoring programs including the PGMN, soil moisture, and climate change; 4. The SWP program that helped to advance groundwater information in Ontario through the water budgets and modeling exercises; 5. Other modeling including the Conservation Authorities Moraine Coalition's YPDT 3-D model; 6. Participation in special projects for the development of a Low Water Response groundwater indicator and soil moisture; 7. Participation in the development of the annex 8 groundwater report under the Great Lakes Water Quality Agreement; and 8. Partnerships with the Ontario Geological Survey investigating locally important geologic features that have an impact on water quantity and quality.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.425
Threshold uncertainty score0.981

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0060.001
Scholarly communication0.0050.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2930.051

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 head0.086
GPT teacher head0.373
Teacher spread0.287 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2016
Admission routes1
Has abstractyes

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