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Record W4409324838 · doi:10.1063/4.0000499

ACA Video Library (AVL) Update.

2025· article· en· W4409324838 on OpenAlexaff
Allen G. Oliver, Alain M. Beauparlant, Karen C. Glass, Matthew Brown, Tiffany L. Kinnibrugh, Yinka Olatunji-Ojo, Charlotte Stern, Kristina Vitale, Kristin Stevens

Bibliographic record

VenueStructural Dynamics · 2025
Typearticle
Languageen
FieldComputer Science
TopicVideo Analysis and Summarization
Canadian institutionsUniversity of British Columbia, Okanagan CampusKelowna General HospitalUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceInformation retrieval

Abstract

fetched live from OpenAlex

The ACA Video Library (AVL) is a collection of educational and insightful videos on various scientific topics. The AVL is continuously being developed and expanding, with generous support from the American Institute of Physics. Website maintenance is in place and we are accepting submissions. This presentation will inform the membership about goals and updates for this valuable resource. Further details can be found at: https://avl.memberclicks.net

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.529
Threshold uncertainty score0.672

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0010.000
Scholarly communication0.0050.005
Open science0.0030.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.5290.446

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 head0.002
GPT teacher head0.209
Teacher spread0.207 · 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
GenreSoftware

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
Published2025
Admission routes1
Has abstractyes

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