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2022· article· W4220901743 on OpenAlexaff
S. Wahyudin, Mukhammad Rizqy Firdaus Hidayatullah

Bibliographic record

VenueBusiness Journal Jurnal Bisnis Dan Sosial · 2022
Typearticle
Language
FieldBusiness, Management and Accounting
TopicConsumer Behavior and Marketing Influence
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsLikert scaleProduct (mathematics)RespondentStatisticsDescriptive statisticsQuality (philosophy)Simple random sampleScale (ratio)Variable (mathematics)MathematicsGeographyPopulationMedicine

Abstract

fetched live from OpenAlex

This study aims to determine the effect of product design and product quality on consumer purchasing decisions of Saint Barkley in the Bandung Region. The research method used is descriptive quantitative research method. Research data obtained from the distribution of questionnaires. The respondent selection technique is simple random sampling with a total of 100 people. The scale model used is the Likert scale and uses descriptive analysis. Product Design variable with the percentage score of the Product Design variable questionnaire is 56.04% in the interval position 52% - 68% in the less good category. And the Product Quality variable with Product Quality variable is 81.28% in the 68% - 84% interval position in the good category.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.991
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.019
GPT teacher head0.235
Teacher spread0.216 · 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.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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