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Chest X-ray

Computed tomography

Continuous positive pressure ventilation

Spontaneous pneumothorax

Saturation of peripheral oxygen

Fractional inspired oxygen

Standard deviation.

Acknowledgement

The authors wish to acknowledge the Section of Neonatology, Department of Paediatrics, and University of Calgary for their support in conducting this study. We would also like to thank Michelle Matthews, a data management clerk for her help in generating a patient list according to ICD codes.

Financial disclosure

The authors have no financial relationships relevant to this article to disclose.

Funding source

No funding was secured for this study.

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Authors’ original file for figure 1
12887_2014_1136_MOESM2_ESM.pdf Authors’ original file for figure 2

The authors declare that they have no competing interests.

HS. Has conceptualized and designed the study, drafted the initial manuscript, and approved the final revised manuscript as submitted. YR. Analyzed the results, reviewed and revised the manuscript, and approved the final revised manuscript as submitted. AM. Designed the statistical model, carried out the data analyses, reviewed and revised the manuscript, and approved the final revised manuscript as submitted. MK. Critically reviewed and revised the manuscript, and approved the final revised manuscript as submitted. HA. Critically reviewed and revised the manuscript, and approved the final revised manuscript as submitted. AA. Critically reviewed and revised the manuscript, and approved the final revised manuscript as submitted. AL. Conceptualized, helped in the designed study, critically reviewed and revised the manuscript from inception to the final manuscript. All authors read and approved the final manuscript.

Department of Pediatrics, University of Calgary, Foothills Medical Centre, Calgary, Canada
Alberta Health Services, Calgary, Canada
Alberta Children’s Hospital Research Institute, Calgary, Canada
Department of Obstetrics Gynecology, University of Calgary, Calgary, Canada
Community Health Sciences, University of Calgary, Calgary, Canada

Pre-publication history

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated.

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User-generated content has never been more abundant and thriving than today.

With social media, everyone is a publisher; everyone is a photographer; and everyone has an opinion.

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In this guide to user-generated content:

User-generated content (or UGC for short) refers to any content (typically digital) that is created and shared by consumers or fans of a brand, about that brand. This includes anything from a casual Instagram post or Tweet, to something intentional, like a review or testimonial.

For example, let’s say you’ve just purchased a latte from your favorite coffee shop. Today they’ve done a particularly amazing job at creating that latte art swirl you love so much, and you just need to share this. So you snap up a pic and post it to Instagram.

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It’s in the name: user-generated content — content made by users . UGC is unbiased and created without an agenda. As a result, people perceive this kind of content to be more trustworthy, truthful, and authentic.

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Experimental evidence suggests that all of these representations are used by at least some listeners in some listening situations. Clearly, absolute pitch representations are available only to a minority of listeners -- those with perfect pitch. Musical coding may involve several concurrent representations; Dowling (1978), for example, has proposed that for melodies, the most important pitch-related representations are scale degree and contour. Despite the research, little is known at the moment about the mental coding of music.

In some circumstances, knowledge of the precise nature of the mental representation may not be important. A useful way to illustrate this is provided by information theory. The field of information theory (Shannon, 1948; Shannon Weaver, 1949) has provided useful mathematical techniques for characterizing the probablistic relationships between events. Information theory inspired a number of music theorists throughout the 1950s and early 1960s. However, it was abandoned (for reasons that are not entirely clear) by about the mid 1960s. [2] Information theory provides a way to measure contingent probabilities. When rolling dice, for example, we know that the number rolled is independent of numbers previously rolled (this is true even for loaded dice). By contrast, other events exhibit contingent effects as when the occurrence of the letter "u" in English text is considerably increased when preceded by the letter "q".

Figure 6 plots the flow of information for the tune Pop Goes the Weasel. Information is plotted (in bits) for five different representations. For example, the upper-most plot shows information according to the probabilities of different scale degrees. The probabilities used in Fig. 6 were derived from an analysis of roughly 6,000 Western European folk songs.

Notice that the information for both scale degree and melodic interval representations peak at the word "pop". For scale degree diad and interval diad the word "pop" coincides with the second highest information value -- with the maximum value following immediately after the word "pop". There appears to be an element of musical "surprise" at this point that is echoed in the lyrics. As a children's action song, this point is usually accompanied by some abrupt action, also suggestive of surprise.

Note, however, that there is no comparable information peak for metric position. That is, the interval/pitch/scale-degree may be relatively surprising, but the moment of its occurrence is not surprising. This highlights a distinction that can be made between the what and when of surprise. In some musical situations, the "what" is expected, whereas the "when" may be relatively unexpected. A well-known example is evident in the popular "Ode to Joy" from Beethoven's Ninth Symphony, where one of the phrases begins a beat early.

With the exception of the metric position information, all of the pitch-related information values are positively correlated. Table 2 shows a correlation matrix for the information content (measured in bits) for the various representations used in the above analysis of Pop Goes the Weasel . An analysis of a sample of 200 melodies from American, Chinese, Dutch, Pawnee, and Xhosa sources confirms that these positive correlations are endemic.

This material was adapted from the Carnegie Mellon University open learning statistics course available at http://oli.cmu.edu and is licensed under a Creative Commons License. Other materials used in this project are referenced when they appear.

If you have found these materials helpful, DONATE by clicking on the "MAKE A GIFT" link below or at the top of the page! The Department of Biostatistics will use funds generated by this Educational Enhancement Fund specifically towards biostatistics education.

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