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Record W4392399903 · doi:10.4095/332503

Summary of GEM results: Manitoba Far North Geomapping Initiative

2024· report· en· W4392399903 on OpenAlexaffabout
Carola Bohm, N M Rayner

Bibliographic record

Venuenot available
Typereport
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsGeographyHistoryArchaeologyPolitical science

Abstract

fetched live from OpenAlex

The far north of Manitoba is endowed with potential for base and precious metals, diamonds, uranium, and rare metals. The goal of a collaborative project between the Manitoba Geological Survey and the Geological Survey of Canada was to provide an advanced framework of geoscience knowledge for mineral exploration and land-use management. Bedrock mapping, geophysical surveys, and geochemical and geochronological analyses carried out in 2005 to 2011 in the far north of Manitoba showed diverse and complex rocks that record nearly two billion years of Earth history. Key advancements in understanding include a new stratigraphy and chronology of at least four metasedimentary cover sequences in the Seal River Domain, some with high potential for economic uranium, gold, and/or rare-metal mineralization; and the identification of a Neoarchean greenstone belt in the Great Island area with known gold occurrences. The discovery of remnants of ancient (3.5 Ga) cratonic lithosphere in the Seal River area also renders the region favourable for diamond exploration.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.200
Threshold uncertainty score0.402

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.010
Science and technology studies0.0020.000
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0370.021

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 head0.140
GPT teacher head0.407
Teacher spread0.266 · 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 designObservational
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
Published2024
Admission routes2
Has abstractyes

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