Bibliographic record
Abstract
Abstract - We all be familiar with two well-known forms of Carbon which are diamond and graphite. Diamond is a one of the toughest and hard material in the earth. Graphite is well-known as most brittle material. But one thing had changed forever, when two physicists A.K.Geim and K.S. Novoselov had got noble prize for “Graphene”. On the basis of his research work published title” The rise of Graphene”. His work shows that Graphene is 200 times stronger than cast iron. It have so many desirable qualities to use in our daily life. Graphene, becoming eminent as a true 2-D material, had got ever-increasing attention due to its unmatched physicochemical properties (excellent conductivity, high surface area, high mechanical strength ,ease of functionalization and mass production). Graphene is a extraordinarily amazing material with countless highest extents to its name. It is the thinnest material in the universe and the strongest yet calculated. Its charge carriers exhibit massive inherent mobility, have the negligible effective mass (it is zero) and can travel micrometer-long distances without scattering at room temperature. Graphene be able to uphold current densities 6 orders higher than copper, shows record thermal conductivity and stiffness, is impermeable to gases and reconciles such contradictory qualities as brittleness and ductility. Electron transport in graphene is described by a Dirac-like equation.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".