Bibliographic record
Abstract
Bisnis kuliner Applebee’s di Amerika Serikat pernah mengalami masa kenaikan (rise). Namunsejak tahun 2015 industri kuliner ini mengalami tren penurunan (fall). Studi ini bertujuan untukmengetahui alasan penurunan (fall) dan kenaikan (rise) pada bisnis Applebee’s. Studi inimenggunakan studi kasus tunggal pada bisnis Applebee’s yang bergerak di bidang kulinerdengan analisis business model canvas, business pattern, business environment & valueproposition canvas. Bisnis Applebee’s pernah tren pertumbuhan dan sukses karena memilikivalue proposition restoran yang menyediakan berbagai menu minuman berbeda setiap bulannyadengan harga yang sangat terjangkau dan relatif murah yaitu sekitar $1 hingga $3. Namun, bisniskuliner ini mengalami tren penurunan karena value proposition menu yang ditawarkan untukvegetarian sangat terbatas. Studi merekomendasikan key activities membuka 1.700 cabang yangberlokasi di berbagai wilayah Amerika Serikat agar jangkauan customers menjadi lebih mudah.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".