Consultant tender / Muhammad Ammar Zakir Mohd Zamry
Bibliographic record
Abstract
This internship report serves the purpose to record the details of my industrial training which was conducted in MMN Bina Sdn Bhd, which is one of the construction company in Kuantan area. This report will cover the details of my internship in the Development for duration of 5 months which began from 23 August till 7 January, 2021 at MMN Bina Sdn Bhd which is located at Semambu, Kuantan, Pahang.Student who are undertaking the course name Diploma in University Technology MARA (UITM) are compulsory to undergo an industrial training at one of the company for a period of 5 months prior to graduating. Student are allowed to make their own choices to enter any company to do their internship, as long as have building background. This is to ensure students will be getting the exposure to involve in building related works instead of other non- building related works. The objectives of this industrial training are to develop a deeper understanding on the course which they are undertaking and to provide the appropriate work-related trainings to them in the field of civil profession.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.359 | 0.118 |
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".