Bibliographic record
Abstract
Biological weapon had been used by Assyrians to poisoned their enemy in 6th century B.C., in 1346 Mongol warriors of the Golden Horde died of plague and their bodies were thrown over the walls of Crimean city Kaffa, resulting in the killing of estimated 25 million Europeans, The British Army used small pox against native Americans during the siege of Fort Pitt in 1763, resulting in the killing of estimated one hundred native Americans in Ohio country in 1764, during the world war 1 imperial German government used anthrax and glanders and became encourage to produce biological weapon because of its advancement through bacteriology and germ theory in 1900, as germ warfare, is produced by biological toxins or infectious agents like bacteria, viruses, fungi(living organisms) and perhaps lethal or non-lethal etc. who are universally recognized as dead but reproduces by making of biological weapons to kill humans, animals, plants or to devastates entire universe, effects of biological war is similar to nuclear war, it can wipeout an entire community or an entire civilization from the universe, attack by insects over enemies is called entomological warfare, entomological weapon is recognized as biological weapon, biological weapon, chemical weapon and nuclear weapon are different kinds but they are not conventional warfare, the war is for universal devastation, biological weapon uses for strategic advantage over enemy either by threat or deployment, also known as area denial weapon, it can be deployed, stockpiled, or developed by individual, terrorist or a nation state over their enemy. As a student and a researcher of the area in international development and international affairs, I always would like to explore areas which can be useful for the knowledge and information and can be a message to the world for its security, I am interested to pursue my PhD in the areas of international development and writing articles is a part of my preparedness for my higher studies.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".