🕷️ Crawler Inspector

URL Lookup

Direct Parameter Lookup

Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 129 (from laksa175)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa129.int.ahrefs:8124/' \
  -H 'Content-Type: text/plain' \
  -H 'X-ClickHouse-Database: crawler3' \
  -H 'Authorization: Basic YXBpOg==' \
  -d 'SELECT getAhrefsURLFromUnparsed(src_unparsed) AS found_url, ifNull(toUnixTimestamp(download_stamp), 0) AS crawl_time, ifNull(toUnixTimestamp(props_url_first_seen), 0) AS first_indexed_time, download_http_code AS http_code, src_unparsed AS src_unparsed, src_root_hash AS src_root_hash, history_drop_reason AS history_drop_reason, meta_title AS meta_title, meta_descriptions AS meta_descriptions, attrs_boilerpipe_text AS attrs_boilerpipe_text, attrs_markdown AS attrs_markdown, attrs_readable_markdown AS attrs_readable_markdown, meta_canonical AS meta_canonical FROM crawler3.page_info_local FINAL PREWHERE (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://pubmed.ncbi.nlm.nih.gov/33674922/\')), getAhrefsUnparsedNoserviceFromURL(\'https://pubmed.ncbi.nlm.nih.gov/33674922/\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/pubmed.ncbi.nlm.nih.gov\/33674922\/","crawl_time":1749163420,"first_indexed_time":1632888899,"http_code":200,"src_unparsed":"gov,nih!nlm,ncbi,pubmed,\/33674922\/ s443","src_root_hash":"7295144728021232729","history_drop_reason":"tooold","meta_title":"A Pragmatic Assessment of Google Translate for Emergency Department Instructions","meta_descriptions":["GT for discharge instructions in the ED is inconsistent between languages and should not be relied on for patient instructions."],"attrs_boilerpipe_text":"\n          Background:\n         \n      \n      Because many hospitals have no mechanism for written translation, ED providers resort to the use of automated translation software, such as Google Translate (GT) for patient instructions. A recent study of discharge instructions in Spanish and Chinese suggested that accuracy rates of Google Translate (GT) were high.\n     \n          Study objective:\n         \n      \n      To perform a pragmatic assessment of GT for the written translation of commonly used ED discharge instructions in seven commonly spoken languages.\n     \n          Methods:\n         \n      \n      A prospective assessment of the accuracy of GT for 20 commonly used ED discharge instruction phrases, as evaluated by a convenience sample of native speakers of seven commonly spoken languages (Spanish, Chinese, Vietnamese, Tagalog, Korean, Armenian, and Farsi). Translations were evaluated using a previously validated matrix for scoring machine translation, containing 5-point Likert scales for fluency, adequacy, meaning, and severity, in addition to a dichotomous assessment of retention of the overall meaning.\n     \n          Results:\n         \n      \n      Twenty volunteers evaluated 400 google translated discharge statements. Volunteers were 50% female and spoke Spanish (5), Armenian (2), Chinese (3), Tagalog (4), Korean (2), and Farsi (2). The overall meaning was retained for 82.5% (330\/400) of the translations. Spanish had the highest accuracy rate (94%), followed by Tagalog (90%), Korean (82.5%), Chinese (81.7%), Farsi (67.5%), and Armenian (55%). Mean Likert scores (on a 5-point scale) were high for fluency (4.2), adequacy (4.4), meaning (4.3), and severity (4.3) but also varied.\n     \n          Conclusion:\n         \n      \n      GT for discharge instructions in the ED is inconsistent between languages and should not be relied on for patient instructions.\n    ","attrs_markdown":"# A Pragmatic Assessment of Google Translate for Emergency Department Instructions\nJ Gen Intern Med. 2021 Nov;36(11):3361-3365.   doi: 10.1007\/s11606-021-06666-z.   Epub 2021 Mar 5.\n\n### Authors\n[Breena R Taira](https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Taira+BR&cauthor_id=33674922)  [1](https:\/\/pubmed.ncbi.nlm.nih.gov\/33674922\/#affiliation-1 \"Olive View-UCLA Medical Center, Sylmar, CA, USA. btaira@ucla.edu.\") , [Vanessa Kreger](https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Kreger+V&cauthor_id=33674922)  [2](https:\/\/pubmed.ncbi.nlm.nih.gov\/33674922\/#affiliation-2 \"Olive View-UCLA Medical Center, Sylmar, CA, USA.\") , [Aristides Orue](https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Orue+A&cauthor_id=33674922)  [2](https:\/\/pubmed.ncbi.nlm.nih.gov\/33674922\/#affiliation-2 \"Olive View-UCLA Medical Center, Sylmar, CA, USA.\") , [Lisa C Diamond](https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Diamond+LC&cauthor_id=33674922)  [3](https:\/\/pubmed.ncbi.nlm.nih.gov\/33674922\/#affiliation-3 \"Memorial Sloan Kettering Cancer Center, New York, NY, USA.\")\n\n### Affiliations\n- 1 Olive View-UCLA Medical Center, Sylmar, CA, USA. btaira@ucla.edu.\n- 2 Olive View-UCLA Medical Center, Sylmar, CA, USA.\n- 3 Memorial Sloan Kettering Cancer Center, New York, NY, USA.\n\n- PMID:   [33674922](https:\/\/pubmed.ncbi.nlm.nih.gov\/33674922\/)\n- PMCID:   [PMC8606479](https:\/\/pmc.ncbi.nlm.nih.gov\/articles\/PMC8606479\/)\n- DOI:   [10\\.1007\/s11606-021-06666-z](https:\/\/doi.org\/10.1007\/s11606-021-06666-z)\n\n## Abstract\n**Background:**  Because many hospitals have no mechanism for written translation, ED providers resort to the use of automated translation software, such as Google Translate (GT) for patient instructions. A recent study of discharge instructions in Spanish and Chinese suggested that accuracy rates of Google Translate (GT) were high.\n\n**Study objective:**  To perform a pragmatic assessment of GT for the written translation of commonly used ED discharge instructions in seven commonly spoken languages.\n\n**Methods:**  A prospective assessment of the accuracy of GT for 20 commonly used ED discharge instruction phrases, as evaluated by a convenience sample of native speakers of seven commonly spoken languages (Spanish, Chinese, Vietnamese, Tagalog, Korean, Armenian, and Farsi). Translations were evaluated using a previously validated matrix for scoring machine translation, containing 5-point Likert scales for fluency, adequacy, meaning, and severity, in addition to a dichotomous assessment of retention of the overall meaning.\n\n**Results:**  Twenty volunteers evaluated 400 google translated discharge statements. Volunteers were 50% female and spoke Spanish (5), Armenian (2), Chinese (3), Tagalog (4), Korean (2), and Farsi (2). The overall meaning was retained for 82.5% (330\/400) of the translations. Spanish had the highest accuracy rate (94%), followed by Tagalog (90%), Korean (82.5%), Chinese (81.7%), Farsi (67.5%), and Armenian (55%). Mean Likert scores (on a 5-point scale) were high for fluency (4.2), adequacy (4.4), meaning (4.3), and severity (4.3) but also varied.\n\n**Conclusion:**  GT for discharge instructions in the ED is inconsistent between languages and should not be relied on for patient instructions.\n\n**Keywords:**  communication barriers; language services; machine translation; translation.\n\n© 2021. The Author(s).\n\n## MeSH terms\n- Emergency Service, Hospital\n- Female\n- Humans\n- Language\n- Male\n- Patient Discharge\n- Prospective Studies\n- Search Engine\\*\n- Translating\\*\n\n## Grants and funding\n- [P30 CA008748\/CA\/NCI NIH HHS\/United States](https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=P30+CA008748%2FCA%2FNCI+NIH+HHS%2FUnited+States%5BGrants+and+Funding%5D&sort=date&sort_order=desc \"All articles for grant P30 CA008748\/CA\/NCI NIH HHS\/United States\")","attrs_readable_markdown":null,"meta_canonical":null}

3. Robots.txt Check

Query:

Response:

4. Spam/Ban Check

Query:

Response:

5. Seen Status Check

ℹ️ Skipped - page is already crawled

🚫

NOT INDEXABLE

✅

CRAWLED

10 months ago

🤖

ROBOTS ALLOWED

Page Info Filters

Filter	Status	Condition	Details
HTTP status	PASS	`download_http_code = 200`	HTTP 200
Age cutoff	FAIL	`download_stamp > now() - 6 MONTH`	10.2 months ago
History drop	FAIL	`isNull(history_drop_reason)`	tooold
Spam/ban	PASS	`fh_dont_index != 1 AND ml_spam_score = 0`	ml_spam_score=0
Canonical	PASS	`meta_canonical IS NULL OR = '' OR = src_unparsed`	Not set

Page Details

Property	Value
URL	https://pubmed.ncbi.nlm.nih.gov/33674922/
Last Crawled	2025-06-05 22:43:40 (10 months ago)
First Indexed	2021-09-29 04:14:59 (4 years ago)
HTTP Status Code	200
Meta Title	A Pragmatic Assessment of Google Translate for Emergency Department Instructions
Meta Description	GT for discharge instructions in the ED is inconsistent between languages and should not be relied on for patient instructions.
Meta Canonical	null
Boilerpipe Text	Background: Because many hospitals have no mechanism for written translation, ED providers resort to the use of automated translation software, such as Google Translate (GT) for patient instructions. A recent study of discharge instructions in Spanish and Chinese suggested that accuracy rates of Google Translate (GT) were high. Study objective: To perform a pragmatic assessment of GT for the written translation of commonly used ED discharge instructions in seven commonly spoken languages. Methods: A prospective assessment of the accuracy of GT for 20 commonly used ED discharge instruction phrases, as evaluated by a convenience sample of native speakers of seven commonly spoken languages (Spanish, Chinese, Vietnamese, Tagalog, Korean, Armenian, and Farsi). Translations were evaluated using a previously validated matrix for scoring machine translation, containing 5-point Likert scales for fluency, adequacy, meaning, and severity, in addition to a dichotomous assessment of retention of the overall meaning. Results: Twenty volunteers evaluated 400 google translated discharge statements. Volunteers were 50% female and spoke Spanish (5), Armenian (2), Chinese (3), Tagalog (4), Korean (2), and Farsi (2). The overall meaning was retained for 82.5% (330/400) of the translations. Spanish had the highest accuracy rate (94%), followed by Tagalog (90%), Korean (82.5%), Chinese (81.7%), Farsi (67.5%), and Armenian (55%). Mean Likert scores (on a 5-point scale) were high for fluency (4.2), adequacy (4.4), meaning (4.3), and severity (4.3) but also varied. Conclusion: GT for discharge instructions in the ED is inconsistent between languages and should not be relied on for patient instructions.
Markdown	# A Pragmatic Assessment of Google Translate for Emergency Department Instructions J Gen Intern Med. 2021 Nov;36(11):3361-3365. doi: 10.1007/s11606-021-06666-z. Epub 2021 Mar 5. ### Authors [Breena R Taira](https://pubmed.ncbi.nlm.nih.gov/?term=Taira+BR&cauthor_id=33674922) [1](https://pubmed.ncbi.nlm.nih.gov/33674922/#affiliation-1 "Olive View-UCLA Medical Center, Sylmar, CA, USA. btaira@ucla.edu.") , [Vanessa Kreger](https://pubmed.ncbi.nlm.nih.gov/?term=Kreger+V&cauthor_id=33674922) [2](https://pubmed.ncbi.nlm.nih.gov/33674922/#affiliation-2 "Olive View-UCLA Medical Center, Sylmar, CA, USA.") , [Aristides Orue](https://pubmed.ncbi.nlm.nih.gov/?term=Orue+A&cauthor_id=33674922) [2](https://pubmed.ncbi.nlm.nih.gov/33674922/#affiliation-2 "Olive View-UCLA Medical Center, Sylmar, CA, USA.") , [Lisa C Diamond](https://pubmed.ncbi.nlm.nih.gov/?term=Diamond+LC&cauthor_id=33674922) [3](https://pubmed.ncbi.nlm.nih.gov/33674922/#affiliation-3 "Memorial Sloan Kettering Cancer Center, New York, NY, USA.") ### Affiliations - 1 Olive View-UCLA Medical Center, Sylmar, CA, USA. btaira@ucla.edu. - 2 Olive View-UCLA Medical Center, Sylmar, CA, USA. - 3 Memorial Sloan Kettering Cancer Center, New York, NY, USA. - PMID: [33674922](https://pubmed.ncbi.nlm.nih.gov/33674922/) - PMCID: [PMC8606479](https://pmc.ncbi.nlm.nih.gov/articles/PMC8606479/) - DOI: [10\.1007/s11606-021-06666-z](https://doi.org/10.1007/s11606-021-06666-z) ## Abstract Background: Because many hospitals have no mechanism for written translation, ED providers resort to the use of automated translation software, such as Google Translate (GT) for patient instructions. A recent study of discharge instructions in Spanish and Chinese suggested that accuracy rates of Google Translate (GT) were high. Study objective: To perform a pragmatic assessment of GT for the written translation of commonly used ED discharge instructions in seven commonly spoken languages. Methods: A prospective assessment of the accuracy of GT for 20 commonly used ED discharge instruction phrases, as evaluated by a convenience sample of native speakers of seven commonly spoken languages (Spanish, Chinese, Vietnamese, Tagalog, Korean, Armenian, and Farsi). Translations were evaluated using a previously validated matrix for scoring machine translation, containing 5-point Likert scales for fluency, adequacy, meaning, and severity, in addition to a dichotomous assessment of retention of the overall meaning. Results: Twenty volunteers evaluated 400 google translated discharge statements. Volunteers were 50% female and spoke Spanish (5), Armenian (2), Chinese (3), Tagalog (4), Korean (2), and Farsi (2). The overall meaning was retained for 82.5% (330/400) of the translations. Spanish had the highest accuracy rate (94%), followed by Tagalog (90%), Korean (82.5%), Chinese (81.7%), Farsi (67.5%), and Armenian (55%). Mean Likert scores (on a 5-point scale) were high for fluency (4.2), adequacy (4.4), meaning (4.3), and severity (4.3) but also varied. Conclusion: GT for discharge instructions in the ED is inconsistent between languages and should not be relied on for patient instructions. Keywords: communication barriers; language services; machine translation; translation. © 2021. The Author(s). ## MeSH terms - Emergency Service, Hospital - Female - Humans - Language - Male - Patient Discharge - Prospective Studies - Search Engine\* - Translating\* ## Grants and funding - [P30 CA008748/CA/NCI NIH HHS/United States](https://pubmed.ncbi.nlm.nih.gov/?term=P30+CA008748%2FCA%2FNCI+NIH+HHS%2FUnited+States%5BGrants+and+Funding%5D&sort=date&sort_order=desc "All articles for grant P30 CA008748/CA/NCI NIH HHS/United States")
Readable Markdown	null
Shard	129 (laksa)
Root Hash	7295144728021232729
Unparsed URL	gov,nih!nlm,ncbi,pubmed,/33674922/ s443