This is a Distant Reader "study carrel", a set of structured data intended to help the student, researcher, or scholar use & understand a corpus.
This study carrel was created on 2021-05-30 by Eric Morgan <emorgan@nd.edu>. The carrel was created using the Distant Reader cord process, and the input was the result of a query applied to a local mirror of CORD, a data set of scholarly articles on the topic of COVID-19. The actual query was: facet_journal:"J Clin Virol". The results of this query were saved in a cache and transformed into a set of plain text files. All of the analysis -- "reading" -- has been done against these plain text files. For example, a short narrative report has been created. This Web page is a more verbose version of that report.
All study carrels are self-contained -- no Internet connection is necessary to use them. Download this carrel for offline reading. The carrel is made up of many subdirectories and data files. The manifest describes each one in greater detail.
There are 118 item(s) in this carrel, and this carrel is 214,393 words long. Each item in your study carrel is, on average, 2,382 words long. If you dig deeper, then you might want to save yourself some time by reading a shorter item. On the other hand, if your desire is for more detail, then you might consider reading a longer item. The following charts illustrate the overall size of the carrel.
On a scale from 0 to 100, where 0 is very difficult and 100 is very easy, the documents have an average readability score of 52. Consequently, if you want to read something more simplistic, then consider a document with a higher score. If you want something more specialized, then consider something with a lower score. The following charts illustrate the overall readability of the carrel.
By merely counting & tabulating the frequency of individual words or phrases, you can begin to get an understanding of the carrel's "aboutness". Excluding "stop words", some of the more frequent words include:
respiratory, patients, virus, pcr, cov, samples, sars, viruses, detection, study, children, clinical, human, positive, influenza, viral, infection, infections, rt, assay, time, using, assays, covid, results, detected, coronavirus, specimens, test, rna, two, testing, disease, one, sensitivity, acute, cases, used, hrv, associated, real, negative, may, also, rapid, data, table, analysis, tested, severe
Using the three most frequent words, the three files containing all of those words the most are Clinical manifestations and outcomes of respiratory syncytial virus infection in adult hospitalized patients, Comparison of two broadly multiplexed PCR systems for viral detection in clinical respiratory tract specimens from immunocompromised children, and Prospective evaluation of a novel multiplex real-time PCR assay for detection of fifteen respiratory pathogens—Duration of symptoms significantly affects detection rate.
The most frequent two-word phrases (bigrams) include:
respiratory tract, respiratory viruses, acute respiratory, nucleic acid, respiratory syncytial, syncytial virus, time pcr, respiratory virus, human metapneumovirus, tract infections, lower respiratory, respiratory syndrome, cord uid, viral load, clin virol, doc id, virol doi, respiratory infections, novel coronavirus, severe acute, time rt, human bocavirus, pcr assay, influenza viruses, avian influenza, positive samples, influenza virus, pcr assays, human coronavirus, real time, copies ml, reverse transcription, cystic fibrosis, ct values, chain reaction, respiratory specimens, polymerase chain, young children, respiratory samples, hong kong, human rhinovirus, study design, viral infections, hospitalized patients, clinical specimens, viral rna, tract infection, syndrome coronavirus, clinical samples, coronavirus disease
And the three file that use all of the three most frequent phrases are Comparison of two broadly multiplexed PCR systems for viral detection in clinical respiratory tract specimens from immunocompromised children Prospective evaluation of a novel multiplex real-time PCR assay for detection of fifteen respiratory pathogens—Duration of symptoms significantly affects detection rate, and The clinical impact of coronavirus infection in patients with hematologic malignancies and hematopoietic stem cell transplant recipients.
While often deemed superficial or sophomoric, rudimentary frequencies and their associated "word clouds" can be quite insightful:
Sets of keywords -- statistically significant words -- can be enumerated by comparing the relative frequency of words with the number of times the words appear in an entire corpus. Some of the most statistically significant keywords in the carrel include:
sars, pcr, respiratory, virus, rsv, covid-19, patient, hrv, rna, infection, nl63, cov-2, child, oc43, nat, lrti, lamp, influenza, hku1, hiv, h7n9, elisa, dna, d68, csf, cdc, wuv, usa, toci, time, testing, test, telemedicine, strain, scheme, sample, s450, rvp, rv+, rti, rpa, respi, rbd, rad, qpm, qce, protein, probe, presto, nrevss
And now word clouds really begin to shine:
Topic modeling is another popular approach to connoting the aboutness of a corpus. If the study carrel could be summed up in a single word, then that word might be respiratory, and Absence of Melaka-virus in European children with respiratory disease is most about that word.
If the study carrel could be summed up in three words ("topics") then those words and their significantly associated titles include:
If the study carrel could be summed up in five topics, and each topic were each denoted with three words, then those topics and their most significantly associated files would be:
Moreover, the totality of the study carrel's aboutness, can be visualized with the following pie chart:
Through an analysis of your study carrel's parts-of-speech, you are able to answer question beyonds aboutness. For example, a list of the most frequent nouns helps you answer what questions; "What is discussed in this collection?":
patients, virus, samples, viruses, detection, study, children, influenza, infection, infections, assay, time, assays, results, specimens, sensitivity, test, testing, cases, disease, coronavirus, data, analysis, tract, symptoms, tests, sample, studies, diagnosis, days, years, age, laboratory, pneumonia, cells, gene, number, cell, acid, protein, group, amplification, hospital, patient, table, use, prevalence, adults, performance, methods
An enumeration of the verbs helps you learn what actions take place in a text or what the things in the text do. Very frequently, the most common lemmatized verbs are "be", "have", and "do"; the more interesting verbs usually occur further down the list of frequencies:
using, detect, included, tested, showed, associated, performed, compared, identified, reported, based, found, hospitalized, describe, collected, infected, obtained, following, provides, observed, evaluating, caused, increased, requires, developed, suggests, determining, confirm, considered, containing, analyzed, indicated, needed, assess, occurred, isolated, knowing, receive, defined, demonstrated, presented, extracted, remains, reducing, making, acquired, according, allows, result, target
An extraction of proper nouns helps you determine the names of people and places in your study carrel.
SARS, PCR, CoV-2, RT, RNA, HRV, COVID-19, RSV, A, C, J, HCoV, Fig, CoV, Table, EV, B, NL63, HBoV, OC43, HIV, China, RP, H5N1, FilmArray, T, HKU1, Coronavirus, Clin, Virol, Human, sha, DNA, Influenza, CDC, D68, USA, CD4, parainfluenza, LAMP, MERS, Germany, IgG, DOI, Ct, Abbott, S, qPCR, NAT, metapneumovirus
An analysis of personal pronouns enables you to answer at least two questions: 1) "What, if any, is the overall gender of my study carrel?", and 2) "To what degree are the texts in my study carrel self-centered versus inclusive?"
we, our, it, their, its, they, them, i, us, his, her, he, she, one, itself, ourselves, you, usa_wa1/2020, themselves, pgadt7, ours, nsp10, my, il)-2r, him, cord-313375-rs3jjiuj, -procleix
Below are words cloud of your study carrel's proper & personal pronouns.
Learning about a corpus's adjectives and adverbs helps you answer how questions: "How are things described and how are things done?" An analysis of adjectives and adverbs also points to a corpus's overall sentiment. "In general, is my study carrel positive or negative?"
respiratory, clinical, positive, viral, human, acute, real, negative, severe, high, rapid, molecular, diagnostic, different, lower, nucleic, higher, available, novel, low, specific, new, common, nasopharyngeal, syncytial, non, first, similar, significant, avian, single, pediatric, many, direct, sensitive, multiple, genetic, previous, important, several, possible, false, bacterial, routine, multiplex, median, additional, patient, large, analytical
also, however, previously, respectively, well, significantly, now, recently, highly, frequently, even, less, therefore, still, newly, encephalitis, relatively, often, especially, currently, least, approximately, prior, furthermore, mainly, moreover, together, particularly, commonly, first, worldwide, additionally, usually, rather, yet, probably, statistically, rapidly, initially, clinically, subsequently, commercially, routinely, overall, generally, fully, notably, interestingly, directly, similarly
There is much more to a study carrel than the things outlined above. Use this page's menubar to navigate and explore in more detail. There you will find additional features & functions including: ngrams, parts-of-speech, grammars, named entities, topic modeling, a simple search interface, etc.
Again, study carrels are self-contained. Download this carrel for offline viewing and use.
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