Bibliographic record
Abstract
Blessed be Allah, the Best of Creators [23:15]In the early 20th century, researchers began to unravel the great potential of microorganisms to improve the health of humans with the discovery of drugs such as Penicillin. These compounds known as antibiotics are produced by bacteria and fungi to fight off other organisms. It was these revolutionary compounds that transformed modern health care and were key in reducing the burden of infectious diseases, saving millions of lives.Allah says in the Holy Qur'an,And He has subjected to you whatsoever is in the heavens and whatsoever is in the earth: all this is from Him. In that surely are Signs for a people who reflect. [45:14]From cattle to E.coli, it is the great beneficence of Allah that He has gifted humans with the capability to harness the power of nature and His creation. However, when this early work into microorganisms was being undertaken, no one could have predicted the great potential they could have for humans. While it is important to find cures to diseases and other human maladies through directed research, the last 100 years of science has repeatedly shown us that basic science, that is open ended inquisitiveness leads the way in finding new cures and new possibilities.My talk will highlight how basic science research especially into microorganisms such as bacteria and viruses has helped to revolutionize the way we treat diseases and has driven our understanding of the building blocks of life. I will discuss specific examples of the origins of biotechnology, drug discovery, molecular biology, and the latest gene-editing technologies such as CRISPR. My aim will be to inspire and to educate the attendees (both scientific & nonscientific) about the wonders of basic science as a vessel to improve the world.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.011 | 0.017 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.016 |
| Insufficient payload (model declined to judge) | 0.010 | 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".