Bibliographic record
Abstract
二恶英是世界上毒性最大的持久性有机污染物之一，它们可以沿食物网富集放大，对人类健康造成严重危害。建立二恶英排放清单是制定减排战略的关键步骤，也是模拟研究二恶英环境行为和健康风险评估的基础数据。本研究首先基于斯德哥尔摩公约中已发布66个国家二恶英排放量，结合主成分分析法确定影响二恶英排放的主要经济活动因子，构建二恶英排放回归模型；然后基于此模型，估算全球196个国家2002-2012年的二恶英大气排放量，并基于人口密度构建全球网格化二恶英大气排放清单（1°×1°）；利用CanMETOP（Canadian Model for Environmental Transport of Organochlorine Pesticides）模拟二恶英环境归趋行为过程及在各环境介质中的浓度水平。并将模拟的大气浓度与实际观测数据进行比较，以验证排放清单。结果表明，2002-2012年期间，全球二恶英的排放量呈现下降趋势。从空间上看，二恶英排放主要集中在亚洲、非洲和欧洲，其中2012年排放量前五位的是中国（3120 g TEQ）、印度（2583 g TEQ）、肯尼亚（2754 g TEQ）、尼日利亚（2115 g TEQ）、日本（2057 g TEQ）。网格化排放清单结果显示，二恶英在人口密集的中国东南沿海、印度北部、西欧和尼日利亚中部地区排放量较高。二恶英环境模拟结果表明其主要集中在气相，且模拟值和观测值之间显著相关，验证了本研究编制的全球二恶英网格化排放清单的准确性和可靠性。
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".