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Record W3131944304 · doi:10.17632/s3c53pk9g7.1

Gravity and Magnetic data

2020· article· en· W3131944304 on OpenAlexaboutno aff
Abdelhakim Eshanibli

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsGeodesyComputer scienceGeologyPhysics

Abstract

fetched live from OpenAlex

Gravity ground survey data is obtained from the Libyan Petroleum Institute (LPI) located in Tripoli, the capital of Libya. The LPI collaborates with the Libyan Gravity Project (LGP). The LGP obtains data from numerous oil and gas companies working in Libya as well as from the NOC. The gravity data consist of 74,520 data-points taken at 1.0 km separation across the study area based on the Geodetic Reference System 1980 (GRS 80) at 2.67 g/cm³ reduction density. The aeromagnetic data is obtained from the African Magnetic Mapping Project (AMMP). The AMMP is part of a worldwide collaboration between Peterson, Grant and Watson Limited (PGW, Canada), GETECH (United Kingdom) and the International Institute for Geo-Information Science and Earth Observation (ITC, the Netherlands). Flight lines and data-points along each line are both 1.0 km apart. A total of 113 flight lines in the E-W direction and roughly 197 data points along each flight line resulting in about 22,270 magnetic data-points.

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)0.004
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 score0.057
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.010
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0570.037

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 head0.047
GPT teacher head0.227
Teacher spread0.180 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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