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Record W3091301383 · doi:10.24036/107349-0934

Panduan Alih Media Karya Tugas Akhir Teknik Mesin Menggunakan Aplikasi Nitro Pro 8

2019· article· en· W3091301383 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
TopicEdcuational Technology Systems
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsComputer scienceProcess (computing)SoftwareTransfer (computing)NitroOperating systemMultimediaChemistry

Abstract

fetched live from OpenAlex

AbstractTransfer of media to digital format is an alternative choice to preserve the information content of library materials, because this format can be stored on relatively large capacity and durable storage media. In making this Media Transfer guide the Nitro Pro 8 application is used. The reason is that it is easier in the process of transferring information from word to pdf, as well as the availability of various menu options used to support the transfer process. Nitro Pro 8 itself is a software that we can use to read, create, edit and share PDF files. Nitro Pro allows us to process the batch file to convert documents to pdf. Nitro Pro is often called Nitro Pro PDF, which means a very good software for handling PDF files.Keywords: transfer, digital, Nitro Pro 8, library

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0030.001
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 head0.016
GPT teacher head0.229
Teacher spread0.213 · 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