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Record W7064889276

DEHCHO - GREAT RIVER: The State of Science in the Mackenzie Basin (1960-1985)

2016· report· en· W7064889276 on OpenAlexfundno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2016
Typereport
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsnot available
FundersGovernment of Canada
KeywordsSubject (documents)IndigenousStructural basinState (computer science)PoliticsPeriod (music)Order (exchange)
DOInot available

Abstract

fetched live from OpenAlex

The Mackenzie Basin is a unique eco-hydrological zone, a vast store of natural resources, and home to both Indigenous and non-Indigenous peoples. Historically, the Basin has been the subject of political controversy, protection, exploitation, and research in the natural and social sciences. While the Basin’s future is unknown, there are real risks that records documenting past conditions in the Basin will be lost. The goal of this project was to seek out historical documents and data pertaining to the quality of water in the Mackenzie Basin between 1960 and 1985. This initiative, sponsored by The Gordon Foundation, proved to be very timely because of cuts to federal libraries that resulted in the boxing up of large numbers of federal reports and other relevant documents. UNU-INWEH sourced thousands of references from various online databases and private collections. However, hard copies of documents were much more difficult to obtain. While librarians in public libraries and universities were extremely helpful, some documents were stored in locations where access is limited. Other documents could only be ordered through interlibrary loans, which are subject to a maximum number per request and a loan period of two weeks. Thus, the time to source even a small number of documents was in the order of months. There were fortunate developments that mitigated the slow erosion of historical documents. Retiring federal scientists and university professors with personal collections were willing to donate documents in the hope that they would be put to good use and kept safe. This project sheds some light on the importance of historical documents. Trends in development can be aligned with patterns in water quality. Impacts predicted 40 years ago can be evaluated against what actually occurred. On the other hand, some calls for action appear to have gone unheeded. For instance, proposals to develop monitoring programs in the Basin are still being heard more than 40 years after these data gaps were originally recognized. UNU-INWEH feels fortunate to have been involved in this project and to have had an opportunity to evaluate documentation that may have been otherwise lost.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.009
GPT teacher head0.189
Teacher spread0.180 · 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 designQualitative
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

Citations0
Published2016
Admission routes1
Has abstractyes

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