Textural and geochemical characteristics of off shore sediment of North Bay of Bengal：A statistical approach for marine metal pollution
Bibliographic record
Abstract
在这份报纸介绍的孟加拉沉积的诺思海湾的沉积上的金属污染学习基于存在岩石层位学在上游， 42 件沉积样品的矿物学和 geochemical 分析。统计分析识别金属污染以及它的明显的来源在离开岸区域。样品用顺序的抽取方法为谷物尺寸，器官的内容和重金属(Fe， Mn， Cr， Cu， Ni， Pb， Cd， Zn 和公司) 被分析评估 geochemical 过程和污染负担。人为的输入，由象丰富因素那样的量的索引的几条途径包括分类，污染因素，污染的度，污染负担索引和 geo 累积索引以推测，被尝试。金属种形成结果在 Cr 的可氧化的部分的可观的数量同样在 Dhamra 被检测的 Mahanadi 横断沉积的可交换的部分显示 Cd 的高 % 。量的索引由于 Cd 的高水平把孟加拉的诺思海湾放在中等弄脏的地区下面。到 Fe 的金属的正规化为 Cd 和 Cr 显示了相对高的丰富因素。因素分析识别了沉积 pH 为重金属活动性起一个主要作用的 geochemical 协会的七种可能的类型。在象为 Cd 和在沉积在场的 Cr 的更高的 EF 一样的可交换的部分的更高的 Cd 集中可以在沉积的地球化学在最细微的骚乱下面提出第二等的水污染的风险。有近肋骨的地区和在上游的地层学的可得到的数据的比较学习揭示了那个开的演员组采矿，压垂倾倒，基于的矿物质工业自河是为集水区域污染的污染的主要来源。除非严密污染控制标准被使用，孟加拉的海湾是可能的面对金属污染的严肃的威胁现在的免职率。
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".