🕷️ Crawler Inspector

URL Lookup

Direct Parameter Lookup

Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 129 (from laksa091)

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, meta_canonical AS meta_canonical, ml_categories_json AS ml_categories_json, ml_types_json AS ml_types_json, ml_intent_types_json AS ml_intent_types_json, meta_language AS meta_language, attrs_author AS attrs_author, ifNull(toUnixTimestamp(attrs_publish_time), 0) AS attrs_publish_time, ifNull(toUnixTimestamp(attrs_original_publish_time), 0) AS attrs_original_publish_time, ifNull(attrs_is_republished, 0) AS attrs_is_republished, ifNull(attrs_nr_words, 0) AS attrs_nr_words, ifNull(attrs_boilerpipe_nr_words, 0) AS attrs_boilerpipe_nr_words, ifNull(body_ext_links_number, 0) AS body_ext_links_number, ifNull(body_int_links_number, 0) AS body_int_links_number, ifNull(meta_nofollow, 0) AS meta_nofollow, ifNull(meta_noarchive, 0) AS meta_noarchive, ifNull(props_was_rendered, 0) AS props_was_rendered, ifNull(src_redirect, \'\') AS src_redirect, ifNull(download_time_msec, 0) AS download_time_msec, ifNull(download_ttfb_msec, 0) AS download_ttfb_msec, ifNull(download_size, 0) AS download_size FROM crawler3.page_info_local FINAL PREWHERE int_partition_id = 63 AND (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://pmc.ncbi.nlm.nih.gov/articles/PMC7610170/\')), getAhrefsUnparsedNoserviceFromURL(\'https://pmc.ncbi.nlm.nih.gov/articles/PMC7610170/\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/pmc.ncbi.nlm.nih.gov\/articles\/PMC7610170\/","crawl_time":1756204708,"first_indexed_time":0,"http_code":200,"src_unparsed":"gov,nih!nlm,ncbi,pmc,\/articles\/PMC7610170\/ s443","src_root_hash":"7295144728021232729","history_drop_reason":"tooold","meta_title":"CatBoost for big data: an interdisciplinary review - PMC","meta_descriptions":["Gradient Boosted Decision Trees (GBDT’s) are a powerful tool for classification and regression tasks in Big Data. Researchers should be familiar with the strengths and weaknesses of current implementations of GBDT’s in order to use them effectively ..."],"meta_canonical":null,"ml_categories_json":"{\"\/Science\":651,\"\/Science\/Computer_Science\":621,\"\/Science\/Computer_Science\/Machine_Learning_and_Artificial_Intelligence\":598,\"\/Computers_and_Electronics\":570,\"\/Computers_and_Electronics\/Software\":551,\"\/Computers_and_Electronics\/Software\/Software_Utilities\":252}","ml_types_json":"{\"\/Article\":958,\"\/Article\/Study_or_Research_Findings\":765}","ml_intent_types_json":"{\"Informational\":999}","meta_language":"en","attrs_author":null,"attrs_publish_time":0,"attrs_original_publish_time":1756204708,"attrs_is_republished":0,"attrs_nr_words":"25401","attrs_boilerpipe_nr_words":"14150","body_ext_links_number":238,"body_int_links_number":89,"meta_nofollow":1,"meta_noarchive":1,"props_was_rendered":0,"src_redirect":"","download_time_msec":170,"download_ttfb_msec":163,"download_size":108166}

3. Robots.txt Check

Query:

Response:

4. Spam/Ban Check

Query:

Response:

5. Seen Status Check

ℹ️ Skipped - page is already crawled

📍

LOCATION

Host 129 · Partition 63

laksa129

7295144728021232729

🚫

NOT INDEXABLE

✅

CRAWLED

9 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`	9.4 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://pmc.ncbi.nlm.nih.gov/articles/PMC7610170/

Last Crawled

2025-08-26 10:38:28 (9 months ago)

First Indexed

not set

HTTP Status Code

200

Content

Meta Title

CatBoost for big data: an interdisciplinary review - PMC

Meta Description

Gradient Boosted Decision Trees (GBDT’s) are a powerful tool for classification and regression tasks in Big Data. Researchers should be familiar with the strengths and weaknesses of current implementations of GBDT’s in order to use them effectively ...

Meta Canonical

null

Boilerpipe Text

heavy column, fetched on demand

Markdown

heavy column, fetched on demand

Readable Markdown

heavy column, fetched on demand

ML Classification

ML Categories

/Science		65.1%
/Science/Computer_Science		62.1%
/Science/Computer_Science/Machine_Learning_and_Artificial_Intelligence		59.8%
/Computers_and_Electronics		57.0%
/Computers_and_Electronics/Software		55.1%
/Computers_and_Electronics/Software/Software_Utilities		25.2%

Raw JSON

{
    "/Science": 651,
    "/Science/Computer_Science": 621,
    "/Science/Computer_Science/Machine_Learning_and_Artificial_Intelligence": 598,
    "/Computers_and_Electronics": 570,
    "/Computers_and_Electronics/Software": 551,
    "/Computers_and_Electronics/Software/Software_Utilities": 252
}

ML Page Types

/Article		95.8%
/Article/Study_or_Research_Findings		76.5%

Raw JSON

{
    "/Article": 958,
    "/Article/Study_or_Research_Findings": 765
}

ML Intent Types

Informational

99.9%

Raw JSON

{
    "Informational": 999
}

Content Metadata

Language

Author

null

Publish Time

not set

Original Publish Time

2025-08-26 10:38:28 (9 months ago)

Republished

Word Count (Total)

25,401

Word Count (Content)

14,150

Links

External Links

238

Internal Links

Technical SEO

Meta Nofollow

Yes

Meta Noarchive

Yes

JS Rendered

Redirect Target

null

Performance

Download Time (ms)

170

TTFB (ms)

163

Download Size (bytes)

108,166

Location

Host ID

129 (laksa129)

Partition ID

Root Hash

7295144728021232729

Unparsed URL

gov,nih!nlm,ncbi,pmc,/articles/PMC7610170/ s443