User:Afk2231/Quantum machine learning/SladeWillson Peer Review

Peer review
This is where you will complete your peer review exercise. Please use the following template to fill out your review.

General info

 * Whose work are you reviewing? (provide username) - Afk2231
 * Link to draft you're reviewing: User:Afk2231/Quantum machine learning

Lead
Guiding questions:


 * Has the Lead been updated to reflect the new content added by your peer? Yes
 * Does the Lead include an introductory sentence that concisely and clearly describes the article's topic? Yes
 * Does the Lead include a brief description of the article's major sections? I think so
 * Does the Lead include information that is not present in the article? I don't think so
 * Is the Lead concise or is it overly detailed?

Content
Guiding questions:


 * Is the content added relevant to the topic? Yes
 * Is the content added up-to-date? Yes
 * Is there content that is missing or content that does not belong? No
 * Does the article deal with one of Wikipedia's equity gaps? Does it address topics related to historically underrepresented populations or topics? N/A

Tone and Balance
Guiding questions:


 * Is the content added neutral? Yes
 * Are there any claims that appear heavily biased toward a particular position?
 * Are there viewpoints that are overrepresented, or underrepresented?
 * Does the content added attempt to persuade the reader in favor of one position or away from another?

==== Tone and balance evaluation: The tone of the section on quantum machine learning skepticism is a little tricky to judge. While the author of the section remains neutral, the quotes included in the section does appear to persuade the reader in some way. But again, this is quite tricky to judge. ====

Sources and References
Guiding questions:


 * Is all new content backed up by a reliable secondary source of information? Most of it seems to be
 * Are the sources thorough - i.e. Do they reflect the available literature on the topic?
 * Are the sources current?
 * Are the sources written by a diverse spectrum of authors? Do they include historically marginalized individuals where possible?
 * Check a few links. Do they work?

Organization
Guiding questions:


 * Is the content added well-written - i.e. Is it concise, clear, and easy to read?
 * Does the content added have any grammatical or spelling errors? While machine learning algorithms are used to compute immense quantities of data, quantum machine learning increases such capabilities intelligently, quantum machine learning utilizes -> This sentence is incomplete
 * Is the content added well-organized - i.e. broken down into sections that reflect the major points of the topic?

Images and Media
Guiding questions: If your peer added images or media


 * Does the article include images that enhance understanding of the topic?
 * Are images well-captioned?
 * Do all images adhere to Wikipedia's copyright regulations?
 * Are the images laid out in a visually appealing way?

For New Articles Only
If the draft you're reviewing is a new article, consider the following in addition to the above.


 * Does the article meet Wikipedia's Notability requirements - i.e. Is the article supported by 2-3 reliable secondary sources independent of the subject?
 * How exhaustive is the list of sources? Does it accurately represent all available literature on the subject?
 * Does the article follow the patterns of other similar articles - i.e. contain any necessary infoboxes, section headings, and any other features contained within similar articles?
 * Does the article link to other articles so it is more discoverable?

Overall impressions
Guiding questions:


 * Has the content added improved the overall quality of the article - i.e. Is the article more complete?
 * What are the strengths of the content added?
 * How can the content added be improved?

==== Overall evaluation: There isn't much which is added to the article apart from quantum machine learning skepticism, making it difficult to rate the content on a wider spectrum. But the section added seems to be quite interesting. Overall, good work! ====