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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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