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Record W6929695059 · doi:10.5066/p9tzt33j

GIS Data for Geologic and Structure Maps of the Kalispell 1 x 2 Degrees Quadrangle, Montana, and Alberta and British Columbia

2022· dataset· en· W6929695059 on OpenAlexaboutno aff

Bibliographic record

VenueUSGS DOI Tool Production Environment · 2022
Typedataset
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsnot available
Fundersnot available
KeywordsGeologic mapGeospatial analysisGeological surveyScale (ratio)Thematic mapGeographic information systemDigital dataSchema (genetic algorithms)

Abstract

fetched live from OpenAlex

The data release for the geologic and structure maps of the Kalispell 1 x 2 degrees quadrangle, Montana, and Alberta and British Columbia, is a Geologic Map Schema (GeMS)-compliant version that updates the GIS files for the geologic map published in U.S. Geological Survey (USGS) Miscellaneous Investigations Series Map I-2267 (Harrison and others, 2000). The updated digital data present the attribute tables and geospatial features (lines and polygons) in the format that meets GeMS requirements. This data release presents the geologic map as shown on the plates and captured in geospatial data for the published map. Minor errors, such as mistakes in line decoration or differences between the digital data and the map image, are corrected in this version. The database represents the geology for the 16,436 square kilometer, geologically complex Kalispell 1 x 2 degrees Quadrangle, at a publication scale of 1:250,000. The map covers primarily Flathead and Lincoln Counties, but also includes minor parts of Glacier, Lake, and Sanders Counties. These GIS data supersede those in the interpretive report: Harrison, J.E., Cressman, E.R., Whipple, J.W., Kayser, H.Z., Derkey, P.D., and EROS Data Center, 2000, Geologic and structure maps of the Kalispell 1:250,000 quadrangle, Montana, and Alberta and British Columbia: a digital database: U.S. Geological Survey Miscellaneous Investigations Series Map I-2267, version 1.0, 23 p., scale 1:250,000, https://pubs.usgs.gov/imap/i2267/.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.114
Threshold uncertainty score0.381

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.020
Science and technology studies0.0020.000
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1140.039

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 head0.014
GPT teacher head0.208
Teacher spread0.194 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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