🕷️ Crawler Inspector

URL Lookup

Direct Parameter Lookup

Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 31 (from laksa158)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa031.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 = 55 AND (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://www.mdpi.com/2073-431X/13/4/88\')), getAhrefsUnparsedNoserviceFromURL(\'https://www.mdpi.com/2073-431X/13/4/88\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/www.mdpi.com\/2073-431X\/13\/4\/88","crawl_time":1776925010,"first_indexed_time":1711680956,"http_code":200,"src_unparsed":"com,mdpi!www,\/2073-431X\/13\/4\/88 s443","src_root_hash":"11974975279136771031","history_drop_reason":null,"meta_title":"A New Computational Algorithm for Assessing Overdispersion and Zero-Inflation in Machine Learning Count Models with Python","meta_descriptions":["This article provides an overview of count data and count models, explores zero inflation, introduces likelihood ratio tests, and explains how the Vuong test can be used as a model selection criterion for assessing overdispersion. The motivation of this work was to create a Vuong test implementation from scratch using the Python programming language. This implementation supports our objective of enhancing the accessibility and applicability of the Vuong test in real-world scenarios, providing a valuable contribution to the academic community, since Python did not have an implementation of this statistical test."],"meta_canonical":null,"ml_categories_json":"{\"\/Computers_and_Electronics\":806,\"\/Science\":550,\"\/Computers_and_Electronics\/Software\":540,\"\/Science\/Computer_Science\":524,\"\/Science\/Computer_Science\/Machine_Learning_and_Artificial_Intelligence\":521,\"\/Computers_and_Electronics\/Software\/Educational_Software\":314}","ml_types_json":"{\"\/Article\":996,\"\/Article\/Tutorial_or_Guide\":681}","ml_intent_types_json":"{\"Informational\":999}","meta_language":"en","attrs_author":null,"attrs_publish_time":0,"attrs_original_publish_time":1711680956,"attrs_is_republished":0,"attrs_nr_words":"12841","attrs_boilerpipe_nr_words":"7233","body_ext_links_number":151,"body_int_links_number":89,"meta_nofollow":0,"meta_noarchive":0,"props_was_rendered":1,"src_redirect":"","download_time_msec":470,"download_ttfb_msec":466,"download_size":76116}

3. Robots.txt Check

Query:

Response:

4. Spam/Ban Check

Query:

Response:

5. Seen Status Check

ℹ️ Skipped - page is already crawled

📍

LOCATION

Host 31 · Partition 55

laksa031

11974975279136771031

📄

INDEXABLE

✅

CRAWLED

1 month ago

🤖

ROBOTS ALLOWED

Page Info Filters

Filter	Status	Condition	Details
HTTP status	PASS	`download_http_code = 200`	HTTP 200
Age cutoff	PASS	`download_stamp > now() - 6 MONTH`	1.4 months ago
History drop	PASS	`isNull(history_drop_reason)`	No drop reason
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://www.mdpi.com/2073-431X/13/4/88

Last Crawled

2026-04-23 06:16:50 (1 month ago)

First Indexed

2024-03-29 02:55:56 (2 years ago)

HTTP Status Code

200

Content

Meta Title

A New Computational Algorithm for Assessing Overdispersion and Zero-Inflation in Machine Learning Count Models with Python

Meta Description

This article provides an overview of count data and count models, explores zero inflation, introduces likelihood ratio tests, and explains how the Vuong test can be used as a model selection criterion for assessing overdispersion. The motivation of this work was to create a Vuong test implementation from scratch using the Python programming language. This implementation supports our objective of enhancing the accessibility and applicability of the Vuong test in real-world scenarios, providing a valuable contribution to the academic community, since Python did not have an implementation of this statistical test.

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

/Computers_and_Electronics		80.6%
/Science		55.0%
/Computers_and_Electronics/Software		54.0%
/Science/Computer_Science		52.4%
/Science/Computer_Science/Machine_Learning_and_Artificial_Intelligence		52.1%
/Computers_and_Electronics/Software/Educational_Software		31.4%

Raw JSON

{
    "/Computers_and_Electronics": 806,
    "/Science": 550,
    "/Computers_and_Electronics/Software": 540,
    "/Science/Computer_Science": 524,
    "/Science/Computer_Science/Machine_Learning_and_Artificial_Intelligence": 521,
    "/Computers_and_Electronics/Software/Educational_Software": 314
}

ML Page Types

/Article		99.6%
/Article/Tutorial_or_Guide		68.1%

Raw JSON

{
    "/Article": 996,
    "/Article/Tutorial_or_Guide": 681
}

ML Intent Types

Informational

99.9%

Raw JSON

{
    "Informational": 999
}

Content Metadata

Language

Author

null

Publish Time

not set

Original Publish Time

2024-03-29 02:55:56 (2 years ago)

Republished

Word Count (Total)

12,841

Word Count (Content)

7,233

Links

External Links

151

Internal Links

Technical SEO

Meta Nofollow

Meta Noarchive

JS Rendered

Yes

Redirect Target

null

Performance

Download Time (ms)

470

TTFB (ms)

466

Download Size (bytes)

76,116

Location

Host ID

31 (laksa031)

Partition ID

Root Hash

11974975279136771031

Unparsed URL

com,mdpi!www,/2073-431X/13/4/88 s443