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Record W2981472973 · doi:10.4095/288672

Description of watershed outline and water depth survey datasets from Geraldine Lake - Iqaluit, Nunavut

2011· report· en· W2981472973 on OpenAlexaffabout
P Budkewitsch, C Prévost, G Pavlic, M Pregitzer

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsWatershedEnvironmental scienceHydrology (agriculture)GeologyComputer science

Abstract

fetched live from OpenAlex

A watershed outline map, a bathymetric map, and water related statistics of Geraldine Lake, the Iqaluit water supply reservoir where produced following field work in Iqaluit during the summer of 2008. One objective of this initiative was to develop the technology for Nunavut scientists and to transfer the methodologies in communities where drinking water supply is at risk due to a declining supply and a changing climate. With support from Indian and Northern Affairs Canada (INAC), a small team of scientists from the Canada Centre for Remote Sensing (CCRS) are involved in a project to help characterize the water supply of Nunavut communities. This was a complex task involving the delineation of watersheds and estimation of the water volume of the supply lake for the community. To estimate this water volume, a bathymetric map was produced based on field surveys using a depth sounder equipped with a GPS. CCRS developed a low cost and easy to use technique to enable such depth surveys to be rapidly carried out. The technology transfer aspect of the activity was aimed to allow Nunavut professionals to produce lake depth maps with low cost and easy to use tools and software. The enclosed datasets were produced under the ''Enhancing Resilience in a Changing Climate Program'' of the Earth Sciences Sector, Natural Resources Canada. Thousands of depth survey points were acquired between July 25th and August 1st 2008 by CCRS scientists, Nunavut Department of Environment staff, and a teacher of the Nunavut Arctic College. Several large format image maps were printed and distributed to the Municipality of Iqaluit, the Department of Community and Government Services offices in all three regions of Nunavut, the Department of Indian and Northern Affairs, etc., and were presented at several venues. This document describes the digital dataset of Geraldine Lake provided to the Planning and Lands office of the Municipality of Iqaluit.

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)0.000
metaresearch head score (Gemma)0.001
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.312
Threshold uncertainty score0.628

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.008
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.004

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 head0.164
GPT teacher head0.279
Teacher spread0.115 · 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
GenreDataset

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

Citations1
Published2011
Admission routes2
Has abstractyes

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