Impacto de investigaciones sobre grafitización de antracitas durante los años 1960-2018
Bibliographic record
Abstract
espanolEste trabajo describe la contribucion de los investigadores de todo el mundo en el campo de la grafitizacion de antracitas en el periodo comprendido entre 1960 – 2018. Se desarrollo un analisis bibliometrico para examinar las publicaciones cientificas en este campo utilizando las bases de datos Scopus Elsevier, Journal Citation Reports, Scimago Journal & Country Rank y herramientas informaticas. Se analizaron diferentes aspectos de las publicaciones tales como tipo de publicacion, principales areas de investigacion, principales revistas, citaciones,etc. Los articulos publicados provienen principalmente de China, Estados Unidos, Francia, Espana, Japon y Canada con un numero de publicaciones de 75, 37, 32, 27, 18 y 16 respectivamente. Los resultados ayudaran a los investigadores a comprender la situacion actual de la investigacion en el campo de la grafitizacion de antracitas. EnglishThis paper shown the contribution of researchers from around the world in the field of anthracite graphitization in the period from 1960 - 2018. A bibliometric test was developed to examine scientific publications in this field using the Scopus Elsevier databases, Journal Citation Reports, Scimago Journal & Country Rank and computer tools. Different topics of the publications were analyzed such as type of publication, areas of research, main journals, citations among many other aspects. The articles published mainly come from China, the United States, France, Spain, Japan and Canada with several publications of 75, 37, 32, 27, 18 and 16, respectively. The results will help researchers to understand the situation of research in the anthracite graphitization.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.013 | 0.018 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".