init commit
This commit is contained in:
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{
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"name": "Computer Vision Articles Summary",
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"nodes": [
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"name": "Schedule Trigger"
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},
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{
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"parameters": {
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"language": "python",
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"pythonCode": "from bs4 import BeautifulSoup\n\nresults = []\n\n# Loop through incoming items (each should have HTML in `item.json.data`)\nfor item in _input.all():\n html = item.json.get(\"data\", \"\")\n if not html:\n continue\n\n soup = BeautifulSoup(html, \"html.parser\")\n\n # Each paper is defined by <dt> (meta) and <dd> (details)\n for dt, dd in zip(soup.find_all(\"dt\"), soup.find_all(\"dd\")):\n # --- Extract title ---\n title_tag = dd.find(\"div\", class_=\"list-title mathjax\")\n title = (\n title_tag.get_text(strip=True).replace(\"Title:\", \"\")\n if title_tag else \"No title\"\n )\n\n # --- Extract abstract ---\n abstract_tag = dd.find(\"p\", class_=\"mathjax\")\n abstract = (\n abstract_tag.get_text(strip=True)\n if abstract_tag else \"No abstract\"\n )\n\n # --- Extract PDF link ---\n pdf_link = None\n for a in dt.find_all(\"a\"):\n href = a.get(\"href\", \"\")\n if \"pdf\" in href:\n pdf_link = f\"https://arxiv.org{href}.pdf\"\n break\n\n # --- Append one result per paper ---\n results.append({\n \"title\": title,\n \"download\": pdf_link\n })\n\n# Return the list of results. Each dictionary in the list will become a separate item.\nreturn results"
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},
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"type": "n8n-nodes-base.code",
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"typeVersion": 2,
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"id": "9b4702c0-144f-4236-8d5d-ef6d53dfe617",
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"name": "Code in Python (Beta)"
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{
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"parameters": {
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"url": "https://www.arxiv.org/list/cs.CV/recent",
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"sendQuery": true,
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"queryParameters": {
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"sendHeaders": true,
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"headerParameters": {
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"parameters": [
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{
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"name": "accept",
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"value": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7"
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},
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{
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"name": "accept-language",
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"value": "en-US,en;q=0.9,fa;q=0.8"
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},
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"name": "priority",
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"value": "u=0, i"
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"name": "sec-ch-ua",
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"value": "\"Google Chrome\";v=\"141\", \"Not?A_Brand\";v=\"8\", \"Chromium\";v=\"141\""
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"name": "sec-fetch-dest",
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"name": "sec-fetch-mode",
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"value": "navigate"
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"name": "sec-fetch-site",
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"value": "none"
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"name": "sec-fetch-user",
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"value": "?1"
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},
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{
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"name": "upgrade-insecure-requests",
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"value": "1"
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},
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{
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"name": "user-agent",
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"value": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/141.0.0.0 Safari/537.36"
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},
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{
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"name": "cookie",
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"value": "_ga=GA1.1.1933736800.1760440871;_ga_B1RR0QKWGQ=GS2.1.s1760440871$o1$g0$t1760440874$j57$l0$h0;arxiv_labs={%22sameSite%22:%22strict%22%2C%22expires%22:365};captchaAuth=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiJiY2IzOGM4YS1iZGVlLTQ2OTMtOTY5NS1hOWJiMzI0MWU1MGIiLCJleHAiOjE3NjA0NjEzMTksImlwIjoxNTcuMTM4Ljc2LjEyLCJpYXQiOjE3NjA0NTk1MjAsImlzcyI6IkZhc3RseSJ9.MHgyOWQ3NjE2ZjMwNDg0MTkyNjE4MmIwZDczZjA1YWRjODc2ZDE4NmNiMDM0Njg0MWUzNmE0NGRiZDM5YjdkYmM0;"
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"options": {
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"redirect": {
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"redirect": {}
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}
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},
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"type": "n8n-nodes-base.httpRequest",
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"typeVersion": 4.2,
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"position": [
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224,
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],
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"id": "057ea5dc-120c-4603-9d5d-6158f2ae621d",
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"name": "HTTP Request"
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},
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{
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"parameters": {
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"modelId": {
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"__rl": true,
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"value": "models/gemini-2.5-flash",
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"mode": "list",
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"cachedResultName": "models/gemini-2.5-flash"
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},
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"messages": {
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"values": [
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{
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"content": "=Summarize the following article into IEEE-style JSON with the following exact schema:\n\n{\n \"title\": \"string — concise, formal title of the article\",\n \"authors\": [\"Author 1\", \"Author 2\", \"Author 3\"],\n \"affiliation\": \"string — single-line institutional affiliation\",\n \"abstract\": \"string — 2–4 sentences summarizing purpose, method, and conclusion\",\n \"keywords\": [\"keyword1\", \"keyword2\", \"keyword3\", \"keyword4\", \"keyword5\"],\n \"sections\": [\n {\n \"heading\": \"I. Introduction\",\n \"content\": \"2–4 sentences summarizing context and problem statement.\n list here all models used in the article\"\n },\n {\n \"heading\": \"II. Related Work\",\n \"content\": \"2–4 sentences summarizing relevant literature or context.\"\n },\n {\n \"heading\": \"III. Methodology\",\n \"content\": \"2–4 sentences explaining methods or workflow steps.\"\n },\n {\n \"heading\": \"IV. Experimental Results\",\n \"content\": \"2–4 sentences describing findings, metrics, or comparisons.also return the table of results here in html format with 2 - 4 sentence of explaination\"\n },\n {\n \"heading\": \"V. Discussion\",\n \"content\": \"2–4 sentences interpreting results and suggesting implications.\"\n }\n ],\n \"acknowledgment\": \"string — one short sentence acknowledging contributions or support. Also put the link for downloading the article here as 'link': 'url'\"\n}\n\nOutput ONLY valid JSON. Do not include markdown or explanations.\n\nInput article:\ntitle: {{ $json[\"title\"] }}\nlink: {{ $json[\"download\"] }}"
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}
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]
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},
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"jsonOutput": true,
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"options": {}
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},
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"type": "@n8n/n8n-nodes-langchain.googleGemini",
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"typeVersion": 1,
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"position": [
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"id": "d1ad8585-922e-456b-93a4-e644cdcc08f0",
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"name": "Message a model",
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"credentials": {
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"googlePalmApi": {
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"id": "1c9wa457qSf8gf8N",
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"name": "Google Gemini(PaLM) Api account"
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}
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}
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},
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{
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"parameters": {
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"type": "random"
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},
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"type": "n8n-nodes-base.sort",
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"typeVersion": 1,
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"position": [
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640,
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],
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"id": "cf7fda19-d1ad-4600-a3e9-7409936592c4",
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"name": "Sort"
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},
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{
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"parameters": {},
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"type": "n8n-nodes-base.limit",
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"typeVersion": 1,
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"position": [
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"id": "e1fa8189-7c8c-41bd-be8b-5ee32ab8cb8e",
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"name": "Limit"
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},
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{
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"parameters": {
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"mode": "runOnceForEachItem",
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"language": "python",
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"pythonCode": "import json\n\n# Extract and parse the AI output\nraw_text = _input.item.json.content.parts[0].text\nitem = json.loads(raw_text)\n\n# Format it into a structured dictionary\nresults = {\n 'title': str(item.get(\"title\")),\n 'authors': \", \".join(item.get(\"authors\", [])),\n 'affiliation': str(item.get(\"affiliation\")),\n 'abstract': str(item.get(\"abstract\")),\n 'keywords': \", \".join(item.get(\"keywords\", [])),\n 'sections': \"\\n\\n\".join([f\"{sec.get('heading', '')}\\n{sec.get('content', '')}\" for sec in item.get(\"sections\", [])]),\n 'acknowledgment': str(item.get(\"acknowledgment\"))\n}\n\nreturn results"
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},
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"type": "n8n-nodes-base.code",
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"typeVersion": 2,
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"position": [
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"id": "adca7415-7187-4fde-a8fa-94e0378042dd",
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"name": "Code in Python (Beta)1"
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},
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{
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"parameters": {
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"schema": {
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"__rl": true,
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"value": "public",
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"mode": "list",
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"cachedResultName": "public"
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},
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"table": {
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"__rl": true,
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"mode": "list",
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"value": "article"
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},
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"columns": {
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"mappingMode": "autoMapInputData",
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"id"
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"defaultMatch": true,
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"display": true,
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"type": "number",
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"canBeUsedToMatch": true,
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"removed": false
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},
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{
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"id": "title",
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"displayName": "title",
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"required": false,
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"defaultMatch": false,
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"display": true,
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"type": "string",
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"canBeUsedToMatch": true,
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"removed": false
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},
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{
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"id": "authors",
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"canBeUsedToMatch": true,
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},
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{
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"id": "affiliation",
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"displayName": "affiliation",
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"required": false,
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"display": true,
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"type": "string",
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"canBeUsedToMatch": true,
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"removed": false
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},
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{
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"id": "abstract",
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"displayName": "abstract",
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"required": false,
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"defaultMatch": false,
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"display": true,
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"type": "string",
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"canBeUsedToMatch": true,
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"removed": false
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},
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{
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"id": "keywords",
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"displayName": "keywords",
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"required": false,
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"defaultMatch": false,
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"display": true,
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"type": "string",
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"canBeUsedToMatch": true,
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"removed": false
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},
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{
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"id": "sections",
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"displayName": "sections",
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{
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"id": "acknowledgment",
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},
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{
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"id": "created_at",
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"displayName": "created_at",
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"required": false,
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"defaultMatch": false,
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"display": true,
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"type": "dateTime",
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"canBeUsedToMatch": true,
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"removed": false
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}
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"options": {}
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"Code in Python (Beta)": {
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[
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{
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"Message a model": {
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{
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"Limit": {
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||||
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||||
[
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||||
{
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||||
"node": "Message a model",
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"type": "main",
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||||
"index": 0
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||||
}
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||||
]
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||||
]
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},
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||||
"Code in Python (Beta)1": {
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||||
"main": [
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[
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{
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||||
"node": "Insert rows in a table",
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||||
"type": "main",
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||||
"index": 0
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||||
}
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||||
]
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||||
]
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}
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},
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"active": true,
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"settings": {
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"executionOrder": "v1"
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},
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"versionId": "cdc44fdd-e8a4-401b-baa5-c4ccdce1fe00",
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"meta": {
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"templateCredsSetupCompleted": true,
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},
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"id": "Js9yzziCvWSWZmSp",
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||||
"tags": []
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||||
}
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Reference in New Issue
Block a user