Report of the 4th Asian Conference on Environmental Mutagens at CSIR-Indian Institute of Chemical Biology, Kolkata on December 10–12, 2014
Bibliographic record
Abstract
The 4th Asian Conference on Environmental Mutagens was held at CSIR Indian Institute of Chemical Biology, Kolkata, during December 10–12, 2014, in collaboration with All India Congress of Cytology and Genetics. Seventy international delegates from Australia, Austria, Belgium, Canada, China, Germany, Iran, Japan, Kazakhstan, Korea and USA along with 150 Indian delegates and students participated in the conference. The conference was inaugurated by Dr. Takehiko Nohmi, President of the International Association of Environmental Mutagenesis and Genomics Societies and Dr. Ashok K. Giri, President of the Asian Association of Environmental Mutagen Societies. The main objective of the conference was to discuss the present scenario of various hazardous chemicals and environmental pollutants in various areas, and their impacts on human health and scientific measure to combat such environmental threats. The organizer truly thanks those who took part in the conference and made the meet a grand success.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.064 | 0.018 |
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".