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Record W3090260209 · doi:10.24036/107343-0934

Pembuatan Iklan Promosi Perpustakaan Padang Panjang untuk Anak Melalui Media Motion Graphic

2019· article· en· W3090260209 on OpenAlexaff
Grace Wilhelmina, Ardoni Ardoni

Bibliographic record

VenueIlmu Informasi Perpustakaan dan Kearsipan · 2019
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology in Education and Learning
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMotion (physics)Rendering (computer graphics)Computer graphics (images)Graphic designComputer scienceCompositingGraphicsMultimediaArtificial intelligence

Abstract

fetched live from OpenAlex

AbstractThis article discusses the making of Padang Panjang library promotion advertisement for children through motion graphic media. The purpose of writing describes the making of motion graphics to introduce to children. There are 6 stages of making motion graphic as follows: (1) concept or concept, is the stage before making motion graphic, (2) drawing or design, is the stage of making motion graphic more specifically visualized in the form of images, (3) Collection of material or material collecting, is a collection of material in the making of motion graphics, (4) assemblies or assemblies, which are made in several stages, namely designing, animating, compositing, and rendering carried out by using applications, (5) testing or testing the video made, (6) distribution or distribution, is the final stage of packaging and distribution of the product.Keywords: children; library; motion graphic.

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)0.001
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.059
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0590.011

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 head0.210
Teacher spread0.203 · 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
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

Citations1
Published2019
Admission routes1
Has abstractyes

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