Bibliographic record
Abstract
This research is to analyze the content of “Catalyzer” which was published in the past ten years, 27th(1995)-36th(2004) International Chemistry Olympiad (IChO). There are two research purposes to be achieved. First: to analyze the distribution of content of “Catalyzer” in eight categorizes (1.Scientific article, 2.official document, 3.daily schedule, 4.Geography History and Culture, 5.International Exchange, 6.Sight seeing and visiting, 7.Essary, 8.others ) and estimate the percentage of each category. Secondly, the major effort in this research is concentrate on the translation the major category of all “scientific articles” in the Catalyzer into Chinese, and analyze their content. These works can be used as the reference for editors who will edit the “Catalyzer” between 37th IChO and the teaching standard curriculum or materials. The findings in this research are as follows: I. The editorial styles of “Catalyzer” can be categorized by the 3 different ways of treating information of the Journal: (1) collecting data before IChO, or (2) collecting data dynamically, or (3)the balance between them. China(27th), Russia(28th), Canada(29th), Dutch(34th) belong to category (3). Australia(30th), Thailand(31st), German(36th) are dynamically in category (2); Denmark(32nd), India(33rd), Greece(35th) are in category (1). II. The percentage of scientific articles is very different, from 0% to one-third of the total content; and so guesses that the numbers of scientific articles will be related to the methods of editorial “Catalyzer”. III. The contents of scientific articles can be classified into many fields: the introduction of scientists, the history of scientific developing, latest scientific research and the developing of industries. The scientific articles which comes from “Early Catalyzer” was always focused on Science Education, and Histories of Science development. But those in “Recently Catalyzer”, there came the addition of some introduction articles of Modern Scientific Research, and the developments of industries in the host country. The contents of scientific materials can be used as the standard for training the future scientists.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".