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Record W4313547616 · doi:10.1016/j.jsg.2022.104781

West Spitsbergen fold and thrust belt: A digital educational data package for teaching structural geology

2023· article· en· W4313547616 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Structural Geology · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsGeologyForeland basinStructural geologyFold (higher-order function)Historical geologyGeologic mapGeospatial analysisArchipelagoStructural basinEarth sciencePaleontologySeismologyRemote sensingOceanography

Abstract

fetched live from OpenAlex

The discipline of structural geology is taking an advantage of compiling observations from multiple field sites to comprehend the bigger picture and constrain the region's geological evolution. In this study we demonstrate how integration of a range of geospatial digital data sets that relate to the Paleogene fault and thrust belt exposed in the high Arctic Archipelago of Svalbard, is used in teaching in bachelor-level courses at the University Centre in Svalbard. This event led to the formation of the West Spitsbergen Fold and Thrust Belt and its associated foreland basin, the Central Spitsbergen Basin. Our digital educational data package builds on published literature from the past four decades augmented with recently acquired high-resolution digital outcrop models, and 360° imagery. All data are available as georeferenced data containers and included in a single geodatabase, freely available for educators and geoscientists around the world to complement their research and fieldwork with course components from Svalbard.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.032
GPT teacher head0.282
Teacher spread0.249 · 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