Daree Shatie / Nurul Izzatie Mustafa and Nur Aneesa Kamalullail
Bibliographic record
Abstract
Social Media such as Facebook is one of the most effective platforms to start a business. It helps business to reach many customers around the world as they are about 2.8 million monthly active users within the third quarter of 2021. Moreover, social media is the most cost effective way to start a business. In fact, people just need to create an account, sign up for free and start to sell your products. Therefore, Daree Shatie decided to sell thrifted woman’s apparels on these platforms as social media can improve brand awareness because it is the stress-free and profitable digital marketing platforms that can be used to increase business profile. Instead of just focusing on selling, Daree Shatie also want to show to people that they can still be fashionable even though it is from thrifted products and most importantly they can save their money as the price is reasonable and affordable. In this report, it will introduce about Draee Shatie which is a business that selling woman’s apparels. Not only that, in this report, it will explain more details about the business such as the address of the business, organizational chart of Daree Shatie, mission and vision of the business, description of products offered in the business as well as price list for Daree Shatie’s products. In addition, Daree Shatie’s facebook link will be presented in this report, following by the business posting on the Facebook Page which comprises teaser post, Daree Shatie’s hard sells and soft sells copywriting. Both Go-Ecommerce registration and MyENT certificate will be provided in this report as well.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.086 | 0.037 |
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".