Bibliographic record
Abstract
This research used Bibliometric and spatial distribution to describe science research productivities of climate change articles on SCI during 2007-2018. Of 25278 articles on climate change field, total research publication and Article form is increasing from 2007 to 2018; gains 3325 articles of total scientific production; 2800 articles of Article form in 2018 year. Moreover, the Article form is the highest research production as well with 19917 articles (1st ranking). The USA has the highest publication in all the article types and total research productivity (23286 articles with 1st ranking) including 5369 independent articles (23.06%) and 17917 collaborative articles (76.94%). CLIMATIC CHANGE journal has the most research output with 1105 articles (4.37%) and 1st ranking. Vietnam is ranked 45th with 159 articles (0.63%) including 33 independent articles (50th ranking, 20.8%) and 126 collaborative articles (44th ranking, 79.2%). Further, research productivity is also revealed all the countries with different research productivity quantities on the world map as USA, Canada, Europe community, and some Asia countries has high publication. Particular, Independent publication is showed from small red round dot to big one, and cooperative publication is performed in different colors, in which USA has the most publication in dark blue and big red dot. Therefore, this paper revealed science growth, research publishing trend, and spatial distribution of countries on climate change articles, and it also provides knowledge as well as more understanding about climate change field.
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 | 0.004 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.099 | 0.137 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".