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Record W2040219737 · doi:10.1371/journal.pone.0007394

A New Method for Publishing Three-Dimensional Content

2009· article· en· W2040219737 on OpenAlexfundno aff
Eugene Raush, Maxim Totrov, Brian D. Marsden, Ruben Abagyan

Bibliographic record

VenuePLoS ONE · 2009
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsnot available
FundersKnut och Alice Wallenbergs StiftelseKarolinska InstitutetStiftelsen för Strategisk ForskningOntario Genomics InstituteCanadian Institutes of Health ResearchOntario GenomicsGenome CanadaOntario Innovation TrustWellcome TrustGlaxoSmithKline
KeywordsUploadInfographicHyperlinkComputer scienceInformation retrievalVisualizationFile formatDisseminationWorld Wide WebAnnotationElectronic publishingData visualizationPublishingGraphicsData scienceThe InternetData miningWeb pageDatabaseComputer graphics (images)Artificial intelligence

Abstract

fetched live from OpenAlex

A new method for electronic publishing of articles with text linked to its interactive three dimensional content is described. The method is based on a single document containing a variety of objects such as formatted text, multiple three dimensional molecular objects, textured shapes and surfaces, data tables and graphs, chemical spreadsheets, alignments, etc. The 3D article can then be published for an online web delivery using the activeICM/active X components as well as be downloaded as a single file to be browsed with all its attached objects locally with the ICM browser. Both activeICM and ICM browser are freely available for the public. This method eliminates the need for multiple methods for the web and the local off-line delivery; it offers the dramatically enhanced, customizable and interactive delivery of article's three dimensional content and data attachments in a single compact file.

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)0.006
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.991
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.024
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0110.008
Science and technology studies0.0020.002
Scholarly communication0.0090.009
Open science0.0030.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0530.039

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 head0.466
GPT teacher head0.399
Teacher spread0.067 · 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.

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

Citations42
Published2009
Admission routes1
Has abstractyes

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