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Record W4237277353 · doi:10.31219/osf.io/f25mu

perkembangan smartphone oppo diindonesia

2019· preprint· id· W4237277353 on OpenAlexaff
Meyka yulianti

Bibliographic record

Venuenot available
Typepreprint
Languageid
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsHumanitiesMarketing communicationPhysicsArtAdvertisingBusiness

Abstract

fetched live from OpenAlex

Di era globalisasi ini perkembangan teknologi komunikasi semakin berkembang dengan pesat, tidak hanya terjadi di negara-negara maju saja namun negara berkembang seperti Indonesia pun sudah tumbuh dengan pesat. Peranan teknologi komunikasi sangat berpengaruh pada aktvitas seseorang sehari-hari karena dapat membantu seseorang dalam memperoleh dan mencari informasi maupun bertukar informasi dengan yang lain. Salah satu teknologi komunikasi yang saat ini berkembang dengan pesat ialah munculnya telepon pintar atau yang biasa disebut smartphone.Oppo Mobile Communications Co, Ltd adalah produsen elektronik yang bermarkas di Dongguan, Guangdong, Cina. Produk utamanya termasuk MP3 player, pemutar Media portabel, LCD-TV, eBook, pemutar DVD/Cakram Blu- ray dan telepon genggam. Didirikan pada tahun 2004, perusahaan ini telah terdaftar dengan nama merek Oppo di belahan dunia.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.054
Threshold uncertainty score0.181

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0540.016

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 head0.029
GPT teacher head0.275
Teacher spread0.246 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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