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Record W4207085285 · doi:10.5260/chara.23.3.26

Geoscan

2022· article· en· W4207085285 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 Charleston Advisor · 2022
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsNatural resourceGovernment (linguistics)Library scienceService (business)Geological surveyComputer scienceBusinessWorld Wide WebEnvironmental resource managementDatabasePolitical scienceGeologyEnvironmental science

Abstract

fetched live from OpenAlex

Managed by the Government of Canada Publications, GEOSCAN is an Open Access database that collates the Earth Sciences publications of the Natural Resources Canada (NRCAN). Included are almost 90,000 records of Mining, Materials and Energy, Geological Survey of Canada publications, Topographic Maps, Remote Sensing, and Geodesy publications. GEOSCAN offers integrated access services to researchers and students while preserving and disseminating knowledge stemming from Natural Resources Canada's published research and information. It classifies, organizes and disseminates knowledge, providing access to NRCan's publications on topics related to sustainable development, mineral and energy resources and landmass. The database is managed by the Information Management Division of Natural Resources Canada. An Open Access service, GEOSCAN continually adds records and full-text publications as they become available.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.734
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.206
Teacher spread0.193 · 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