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Record W2945969096 · doi:10.1080/17445647.2019.1614489

Geology of the Alpha Regio (V-32) Quadrangle, Venus

2019· article· en· W2945969096 on OpenAlexafffund
Erin Bethell, Richard E. Ernst, C. Samson

Bibliographic record

VenueJournal of Maps · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsÉcole de Technologie SupérieureCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsQuadrangleLineamentGeologyGeologic mapRidgeVenusTerrainGeomorphologyGeodesySeismologyTectonicsCartographyPaleontologyGeographyAstrobiology

Abstract

fetched live from OpenAlex

We present a 1:2,500,000 geological map of the Alpha Regio (V-32) quadrangle, Venus. The V-32 quadrangle extends from 0° to 25 S, 0°to 30° E with an area of approximately 7,600,000 km2. Geological mapping was conducted using full resolution (maximum 75 m/pixel) SAR, altimetry and stereo-derived topography data from NASA's Magellan mission in ArcGIS 10.5. Nearly 40,000 lineaments were mapped. The oldest unit, tessera terrain, is present in two major regions: Alpha Regio and Minu-Anni Tessera. Two major fracture belts, both oriented approximately NNW-SSE, and four minor fracture belts have been identified and characterized. Two previously unrecognized wrinkle ridge trends of radiating and circumferential orientation have also been identified in the northeastern corner of the quadrangle. A total of 77 geological units were mapped. Plains material, previously mapped as global regional plains units, was divided into 27 units. Earlier estimates of the diameters of several coronae have been extended by hundreds of kilometres.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.204
Teacher spread0.195 · 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

Citations10
Published2019
Admission routes2
Has abstractyes

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