MétaCan
Menu
Back to cohort
Record W2126316496 · doi:10.1071/aseg2007ab110

Enhancing the Exploration Process

2007· article· en· W2126316496 on OpenAlexaff
Nigel Phillips, Kenneth A. Hickey, Nick Williams, Dianne Mitchinson, Nicolas Pizarro

Bibliographic record

VenueASEG Extended Abstracts · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsUniversity of British Columbia HospitalMira Geoscience (Canada)
Fundersnot available
KeywordsInversion (geology)GeophysicsGeologyProcess (computing)Context (archaeology)Earth scienceExploration geophysicsComputer sciencePaleontologyTectonics

Abstract

fetched live from OpenAlex

SummaryGeophysics can play an enhanced role in exploration programs when used in conjunction with geology and physical properties. Understanding how geology relates to geophysics is important both for supporting constrained geophysical modelling, and for extracting meaningful information from geophysics. Physical properties, and how geologic processes control physical properties, play a key role to link geology to geophysics and are an important focus of our research. In addition, methods of describing geology in a manner that can be incorporated into geophysical inversions provide another important link between geology and geophysics to aid in the integration process. This information is brought together and applied to deterministic inversion methods that have been developed at the University of British Columbia. When done in the context of a specific exploration goal, earth models can be produced that capture, and are consistent with, available geoscientific information, resulting in a clearer view of the earth.

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)0.005
metaresearch head score (Gemma)0.018
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.028
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0060.010
Open science0.0010.011
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0280.005

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 head0.026
GPT teacher head0.256
Teacher spread0.230 · 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
GenreMethods

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
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueASEG Extended AbstractsSame topicGeological Modeling and AnalysisFrench-language works237,207