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Record W3090686477 · doi:10.24036/107296-0934

Evaluasi Tingkat Keterpakaian Koleksi Perpustakaan di Dinas Perpustakaan dan Kearsipan Kota Padang Panjang

2019· article· en· W3090686477 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
TopicEducational Methods and Media Use
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsLibrary scienceData collectionComputer scienceMathematicsStatistics

Abstract

fetched live from OpenAlex

AbstractThis paper discusses the evaluation of the level of use of library collections in the Padang Panjang Library and Archives Service. The purpose of using this paper is: (1) to describe the compatibility of the use of collections in the Padang Panjang Municipal Library and Archives Service; (2) describe the frequency of use of the library collection; (3) describes the number of collections used by the library.The research method used in testing this final paper is descriptive method. Data collection is done through a process of observation and interviews.The discussion in this paper is calculated from January 2018 to June 2019. The first indicator is to describe the intensity of the use of collections. The number of collections described as a comparison for collections used. The number of collections purchased was 5,257 copies or 27.38% of the 19,197 collections available. And for unused collections, 13,940 copies or 72.62% of the total collection. Based on the number of uses of the collection, only ¼ collections are used and used by users. The second indicator is the frequency of use of collections which are described based on frequency graphs per class. The results of using the graph can be seen the level of usage of the collection per month. For the class with the most collections, the class is 800 with 2,246 copies and the lowest class is 700 with 97 copies. The last indicator is the number of collections used based on the criteria of the year published and the name of the publisher. For the year published from 2015 to 2018 the number of collections used was 1,270 while the publisher's name was approved 5,246 copies. Both of these criteria also oppose the level of use of collections in libraries because these collections are more often used and known by users. Keywords: Usability, collection, amount.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.005
Open science0.0050.002
Research integrity0.0010.002
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 head0.022
GPT teacher head0.283
Teacher spread0.261 · 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