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Record W1985591785 · doi:10.1089/152091502321118874

Using CAVE <sup>®</sup> Technology for Functional Genomics Studies

2002· article· en· W1985591785 on OpenAlexaff
Christoph W. Sensen

Bibliographic record

VenueDiabetes Technology & Therapeutics · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsJavaCaveComputer scienceInterface (matter)WorkstationFunction (biology)Real time JavaOperating systemBiologyEcologyEvolutionary biology

Abstract

fetched live from OpenAlex

We have established the first Java 3D-enabled CAVE (CAVE automated virtual environment). The Java application programming interface allows the complete separation of the program development from the program execution, opening new application domains for the CAVE technology. Programs can be developed on any Java-enabled computer platform, including Windows, Macintosh, and Linux workstations, and executed in the CAVE without modification. The introduction of Java, one of the major programming environments for bioinformatics, into the CAVE environment allows the rapid development applications for genome research, especially for the analysis of the spatial and temporal data that are being produced by functional genomics experiments. The CAVE technology will play a major role in the modeling of biological systems that is necessary to understand how these systems are organized and how they function.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.003

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 head0.050
GPT teacher head0.270
Teacher spread0.220 · 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

Citations12
Published2002
Admission routes1
Has abstractyes

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