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Record W3087307376

SISTEM INFORMASI PENGOLAHAN DATA PERMINTAAN REKAPITULASI BENDA POS UNTUK KANTOR POS CABANG PADA PT. POS INDONESIA (PERSERO) BINJAI BERBASIS WEB

2020· article· id· W3087307376 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

Venuenot available
Typearticle
Languageid
FieldComputer Science
TopicEdcuational Technology Systems
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsObject (grammar)Task (project management)Computer scienceDatabaseArtificial intelligenceManagementEconomics
DOInot available

Abstract

fetched live from OpenAlex

Knowledge and technological developments are currently increasing rapidly, requiring agencies and organizations to use technology to obtain the required information quickly and accurately. PT. Pos Indonesia (Persero) Binjai has a special task of fulfilling requests for postal items required by the Post Branch Offices, therefore PT. Pos Indonesia (Persero) Binjai fulfills requests for postal goods from the respective Branch Post Offices. Processing of postal object recapitulation request data in the form of data on the number of goods, price of goods, and total price. The postal objects are stamps, stamps, envelopes, and postcards. Thus, with the information system processing postal object recapitulation request data, employees can easily obtain postal item request data recapitulation per month.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, 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 score0.504
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.004
Open science0.0100.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.002

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 head0.067
GPT teacher head0.269
Teacher spread0.202 · 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

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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