Beard Brothers’ BBQ / Wan Nurul Hanis Wan Hassan ... [et al.]
Bibliographic record
Abstract
Beard Brothers’ BBQ is a Halal food restaurant that served a variety of meat and was founded in 2013 by Nazri Jameson. Chief Pitmaster Nazri Jameson is a culinary arts graduate who made a decision to take on the responsibility of developing perfectly barbecued halal briskets. His obsession with it had him working for nearly five months, enhancing his strategy and recipe to obtain his perspective of the perfectly barbecued brisket. Beard Brothers’ BBQ can be found in Petaling Jaya, Malaysia. It is a place for people who enjoy eating meat and this is a popular BBQ dish in Malaysia. As we know, the main product for Beard Brothers’ BBQ offered is meat which are halal brisket, ribs and lamb. One of the menus is Colossus which consists smoked beef and lamb, quarter chicken, brotato bun, cornbread and all sauces. Next, for Beard Brothers’ Deli product the types of main sandwiches that they served is New York Pastrami and London Salt Beef. In addition, they also served the ramen broth slow cooked with BBQ meats. Last but not least, they have a variety of side dish but most popular in the Beard Brothers’ BBQ is Apple Pie, Magnolia Banana Pudding and Mac & Cheese. In addition, Beard Brothers’ BBQ promotes their products primarily through social media platforms such as Facebook and Instagram. This is due to the fact that many people will be active on social media, and the platform can attract people to try the foods that are offered. Other than that, they promote their business through marketing agencies and sponsorship marketing. The strength of the company is it has a strategic place where can helps to attract a lot of customers to visit and eat at their restaurant. But the weakness of the restaurant is they did not use delivery such as Grab Food and Food Panda which are popular delivery services. Other than that, one of the opportunities is they have a few small brands under Beard Brothers' BBQ. Last but not least, the threat that they faced is they have many competitors in the same area. Every business today will face numerous challenges and problems. Beard Brothers' BBQ faced several challenges in order to retain their current customers. The first problem when the issues happened because of meat cartel issue. The next problem is Beard Brothers’ BBQ have to do the delivery instead of dine-in due to Movement Control Order (MCO) restriction. The last problem is their product are not available at Grab and Food Panda application.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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.
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 teacher head, 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".