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Record W7019977940

Inventory of land use and land use practices in the Canadian Great Lakes Basin: Report of the International Reference Group on Great Lakes Pollution from Land Use Activities, Volume I, Canadian Great Lakes Basin Summary

2018· report· en· W7019977940 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Atrium (University of Guelph) · 2018
Typereport
Languageen
FieldComputer Science
TopicAdvanced Image Processing Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsLand useStructural basinRecreationVolume (thermodynamics)PollutionDrainage basinHydrology (agriculture)Baseline (sea)
DOInot available

Abstract

fetched live from OpenAlex

This volume presents an Inventory of Land Use and Land Use Practices in the Canadian Great Lakes Basin, with emphasis on certain trends and projections to 1980 (and to 2020 where appropriate). The Task B report for the Canadian part of the Great Lakes Basin is contained in five volumes: Volume I Canadian Great Lakes Basin Summary, Volume II Lake Superior Basin, Volume III Lake Huron Basin, Volume IV Lake Erie Basin, and Volume V Lake Ontario Basin. This volume, Volume I, is the Canadian Great Lakes Basin Summary report. The report integrates several studies by contractors and sub-contractors. These studies were part of the Canadian Task B effort for the Great Lakes Pollution from Land Use Activities Reference Group, International Joint Commission. This report describes and quantifies, as appropriate, the Canadian Great Lakes Basin's geology, soils, minerals, climate, surface and ground water, vegetation, wildlife, and economic and demographic characteristics. It inventories available information on waste disposal operations, lakeshore and riverbank erosion, high-density non-sewered residential areas and recreational land uses, as well as materials application of agricultural chemicals, fertilizers, animal wastes and salts on highways. Finally, future trends and projections are shown for the above categories.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.003
Open science0.0020.000
Research integrity0.0000.001
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 head0.058
GPT teacher head0.259
Teacher spread0.201 · 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