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Record W4409424551 · doi:10.1117/12.3068363

Front Matter: Volume 13302

2025· paratext· en· W4409424551 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typeparatext
Languageen
FieldEngineering
TopicAdvanced Semiconductor Detectors and Materials
Canadian institutionsnot available
FundersUniversity of California, DavisYork UniversityInstitut de Ciències FotòniquesPolytechnique MontréalEmory UniversityCarnegie Mellon UniversityMedizinische Universität WienWashington University School of Medicine in St. LouisGeorgia Institute of TechnologyChildren's Hospital of PhiladelphiaAriel UniversityZhejiang UniversityUniversität WienMassachusetts General Hospital
KeywordsVolume (thermodynamics)Front (military)Computer scienceGeologyPhysicsOceanographyThermodynamics

Abstract

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and subject to review by the editors and conference program committee.Some conference presentations may not be available for publication.Additional papers and presentation recordings may be available online in the SPIE Digital Library at SPIEDigitalLibrary.org.The papers reflect the work and thoughts of the authors and are published herein as submitted.The publisher is not responsible for the validity of the information or for any outcomes resulting from reliance thereon.

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)0.000
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 score0.138
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.8620.757

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 head0.008
GPT teacher head0.223
Teacher spread0.215 · 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".

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Citations0
Published2025
Admission routes1
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