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Record W4231831476 · doi:10.1109/igic.2013.6659117

2013 IGIC technical program

2013· article· en· W4231831476 on OpenAlexaff
Stefan Mozar, Nahum Gershon, Steve Dukes, Paul Navarro, Megan L. Johns, Tzu-Hsun Lu, Heather Martin, Vijay Poduval, Mat Robinson, Andrew Roxby, Michael G. Christel, Leif Oppermann, Lisa Blum, Jun-Yeong Lee, Jung-Hyub Seo, Amber Choo, Mehdi Karamnejad, Peter Quax, Anastasiia Beznosyk, Wouter Vanmontfort, Robin Marx, Wim Lamotte, Rohit Nirmal, Chang Yun, Jenny K. Yi, Martin Le, Patipol Paripoonnanonda, Daniel Johnson, Peta Wyeth, Penny Sweetser, Michele Pirovano, Pier Luca Lanzi, Renato Mainetti, N. Alberto Borghese, Philip J. Harris, Segal Centre, Kim Voll, Elena Bertozzi, H. John, Jennifer D. Parker, Richard Audriusjurgelionis, Lisa Wetzel, Leif Blum, Elizabeth S. Veinott, James Leonard, Mary Magee Quinn, Carl Symborski, Meg Barton, James H. Korris, Travis Falstad, Stephanie Granato, Daniele Loiacono, Jun Fujima, Klaus P. Jantke, Sebastian Arnold, Oksana Arnold, Sebastian Spundflasch, Clyde Blinky, Ross Smith, Chermaine Li, Shilpa Ranganathan, David Mateus, Zotti Finco, Eliseo Bittencourt, Milton Reategui, Kaiyang Zhang, Tim Mcmullan, Shihao Dong, Zhu Guoliang, Danielle Corporon, Salvador Barrera, Héber Fernandes Amaral, José Luís Braga, Aziz Galvão, Christopher Mair, Hellbent Games

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeodetic Measurements and Engineering Structures
Canadian institutionsElectronic Arts (Canada)
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.574
Threshold uncertainty score0.818

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.4260.436

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 head0.006
GPT teacher head0.188
Teacher spread0.182 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2013
Admission routes1
Has abstractno

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