用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills --skill plumx-metrics-api命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
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| name | plumx-metrics-api |
| description | Track research impact beyond citations via PlumX altmetrics API |
| metadata | {"openclaw":{"emoji":"📊","category":"literature","subcategory":"metadata","keywords":["PlumX","altmetrics","research impact","social media metrics","usage statistics","scholarly metrics"],"source":"https://plumanalytics.com/"}} |
PlumX (by Elsevier/Plum Analytics) tracks 5 categories of research impact metrics beyond traditional citations: Usage, Captures, Mentions, Social Media, and Citations. It covers 130M+ research artifacts including articles, datasets, presentations, and videos. Available via Elsevier's API infrastructure. Requires an Elsevier API key.
| Category | What it measures | Examples |
|---|---|---|
| Usage | Reading/viewing | Abstract views, PDF downloads, HTML views |
| Captures | Saving for later | Mendeley readers, CiteULike bookmarks |
| Mentions | Commentary | Blog posts, news articles, Wikipedia refs |
| Social Media | Sharing/discussion | Tweets, Facebook shares, Reddit posts |
| Citations | Formal references | Scopus, CrossRef, PubMed citations |
https://api.elsevier.com/analytics/plumx/
curl -H "X-ELS-APIKey: $ELSEVIER_API_KEY" \
"https://api.elsevier.com/analytics/plumx/doi/10.1038/nature14539"
# By PubMed ID
curl -H "X-ELS-APIKey: $ELSEVIER_API_KEY" \
"https://api.elsevier.com/analytics/plumx/pmid/25428114"
# By ISBN
curl -H "X-ELS-APIKey: $ELSEVIER_API_KEY" \
"https://api.elsevier.com/analytics/plumx/isbn/9780262035613"
# By Scopus ID
curl -H "X-ELS-APIKey: $ELSEVIER_API_KEY" \
"https://api.elsevier.com/analytics/plumx/scopusId/84920765826"
{
"count_categories": [
{
"name": "capture",
"total": 15432,
"count_types": [
{"name": "READER_COUNT", "total": 15432, "sources": [
{"name": "Mendeley", "total": 15432}
]}
]
},
{
"name": "socialMedia",
"total": 3250,
"count_types": [
{"name": "TWEET_COUNT"
import os
import requests
API_KEY = os.environ["ELSEVIER_API_KEY"]
BASE_URL = "https://api.elsevier.com/analytics/plumx"
HEADERS = {"X-ELS-APIKey": API_KEY, "Accept": "application/json"}
def get_plumx_metrics(doi: str) -> dict:
"""Get PlumX metrics for a paper by DOI."""
resp = requests.get(
f"{BASE_URL}/doi/{doi}",
headers=HEADERS,
)
resp.raise_for_status()
data = resp.json()
metrics = {}
for cat in data.get("count_categories", []):
category_name = cat["name"]
metrics[category_name] = {
"total": cat["total"],
"breakdown": {},
}
for ct in cat.get("count_types", []):
metrics[category_name]["breakdown"][ct["name"]] = ct["total"]
return metrics
def compare_impact(dois: list) -> list:
"""Compare PlumX metrics across multiple papers."""
results = []
for doi in dois:
metrics = get_plumx_metrics(doi)
results.append({
"doi": doi,
"citations": metrics.get("citation", {}).get("total", 0),
"captures": metrics.get(, {}).get(, ),
: metrics.get(, {}).get(, ),
: metrics.get(, {}).get(, ),
: metrics.get(, {}).get(, ),
})
results
metrics = get_plumx_metrics()
category, data metrics.items():
()
metric_type, count data[].items():
()
| Feature | PlumX | Altmetric.com | Crossref Event Data |
|---|---|---|---|
| Metric categories | 5 comprehensive | Attention Score | Events only |
| Coverage | 130M+ artifacts | 30M+ outputs | DOI-based |
| Social media | Twitter, Facebook, Reddit | Twitter, Reddit, News | Twitter, Reddit, Wikipedia |
| Usage data | Yes (views, downloads) | No | No |
| Capture data | Yes (Mendeley readers) | Mendeley readers | No |
| Free access | Limited | Limited widget | Full API free |