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Record W1990137764 · doi:10.1145/1399962.1399965

GECCO-2007 highlights

2007· article· en· W1990137764 on OpenAlexaffabout
A. Castellini, Charles Guthrie, B. Yeten, Tina Yu

Bibliographic record

VenueACM SIGEVOlution · 2007
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsChevron (anatomy)Variety (cybernetics)Evolutionary computationWork (physics)Operations researchLibrary scienceEngineeringComputer scienceBiologyArtificial intelligencePaleontologyMechanical engineering

Abstract

fetched live from OpenAlex

The GECCO conference is the largest annual conference in the field of Genetic and Evolutionary Computation. Workshops on specific topics are organized every year. In July 2007, Chevron and Tina Yu from the University of Newfoundland organized the first workshop on Petroleum Applications. Speakers from industry and academia shared their recent work on a variety of subjects and a panel discussion addressed the gaps and opportunities for Oil and Gas companies.

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)0.004
metaresearch head score (Gemma)0.008
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: Commentary · Consensus signal: none
Teacher disagreement score0.084
Threshold uncertainty score0.280

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0070.004
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0840.065

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 head0.016
GPT teacher head0.267
Teacher spread0.251 · 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
GenreCommentary

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
Published2007
Admission routes2
Has abstractyes

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