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  1. Last 7 days
    1. We conducted a qualitative analysis of user study transcripts and survey responses using a Grounded Theory approach [8]. First, the lead researcher collected a list of participants' behaviors, approaches, reflections on their experience, and feedback about the interface. The researcher then systematically coded this data, revisiting the data multiples times and refining the codes to ensure consistency and coherence. Through this process, high-level themes were identified and organized using affinity diagramming. Once the thematic structure was finalized, the researcher gathered supporting evidence for each theme and synthesized the findings, which were reviewed by the research team to ensure agreement on the results.

      sentence describing how analysis was performed on data collected by the authors of this paper

    2. Interviews were video and audio recorded. We transcribed the audio using OpenAI's Whisper automatic speech recognition system and anonymized the transcript before analysis. We analyzed the interview data using thematic analysis [1]. First, two members of the research team independently coded four (25% of collected data) randomly chosen participant data to generate low-level codes. The inter-coder reliability between the coders was 0.88 using Krippendorff's alpha [37]. The two coders then met together to cross-check, resolve coding conflicts, and consolidate the codes into a codebook across two sessions. Using the codebook, the two coders analyzed six randomly selected participant data each. The research team then met, discussed the analysis outcomes, and finalized themes over three sessions.

      sentence describing how analysis was performed on data collected by the authors of this paper

    3. Activity log data, which revealed how participants actually used the interface, echoed the above findings. According to the log data, participants spent most of their reading time (66.31%) with vertical alignment on the second element in structure pairs, followed by alignment on the first element (29.19%), and left-justified alignment (5.13%). Highlighting usage showed a similar preference: 91.13% of time with all chunks highlighted, 8.25% with partial highlighting, and minimal time (0.63%) without highlights.

      sentence describing how analysis was performed on data collected by the authors of this paper

    4. In this section, we present findings on how AbstractExplorer supports comparative close reading at scale by integrating quantitative survey responses and log data with qualitative analysis of transcripts and open-ended responses. The qualitative analysis process is described in detail in Appendix H.

      sentence describing how analysis was performed on data collected by the authors of this paper

    5. Throughout the two tasks, we also collected detailed interaction logs including counts of user-defined aspects created, duration of highlighting usage, and time allocation across the three possible alignment options.

      sentence describing how analysis was performed on data collected by the authors of this paper

    6. Both gaze data and the semi-structured interviews revealed that lower NFC participants were more willing to be guided by the three features and took advantage of them consciously.

      sentence describing how analysis was performed on data collected by the authors of this paper

    7. Using a two-tailed Mann-Whitney U Test, we found that participants who reported their lowest perceived cognitive load when all three features were enabled had significantly lower NFC than participants who reported their lowest cognitive load level when skimming with no features enabled—in the baseline interface (p=0.03).

      sentence describing how analysis was performed on data collected by the authors of this paper

    8. For simplicity of analysis, we denote participants with NFC scores above the overall participants' median NFC of 5.42 (IQR = 0.583) as higher NFC, and lower NFC otherwise.

      sentence describing how analysis was performed on data collected by the authors of this paper

    9. To contrast participants' gaze patterns in each condition, we used a Tobii Pro Spark eye-tracker placed below the desktop monitor used by all subjects; Tobii Pro Lab software recorded each participant's gaze over time in each condition.

      sentence describing how analysis was performed on data collected by the authors of this paper

    10. We collected 80 sentences from our abstracts dataset labeled by our system as "Methodology/Contribution." Participants viewed the same 80 sentences in each condition—often with a different subset of sentences initially visible due to ordering changes—but only had two minutes to look at them in each condition.

      sentence describing how analysis was performed on data collected by the authors of this paper

    11. After obtaining an expanded set of high-level chunk labels, we assign them to each of the sentence chunks by using LLMs in a multiclass classification few-shot learning task, with the initial labels and assignment as examples (see prompt used in Appendix D.3).

      sentence describing how analysis was performed on data collected by the authors of this paper

    12. Then, we segment sentences within each aspect into grammarpreserving chunks (see prompt used in Appendix D.2). This results in grammatically coherent chunks that are the basis of structure patterns. After identifying chunk boundaries, we again prompt an LLM to generate labels for chunks in a human-in-the-loop approach: starting from an initial set of labels for chunk roles, when a new label is generated, a researcher from the research team examines the new label and merges it with existing labels if appropriate, controlling for the total number of labels.

      sentence describing how analysis was performed on data collected by the authors of this paper

    13. We process this data in a three-stage pipeline (Figure 6). In the first stage, Sentence Segmentation and Categorization, abstracts are split into individual sentences using the NLTK package, and each sentence is classified into one of the five pre-defined aspects as listed in Section 4.1.1. Classification is performed by prompting an LLM (see prompt used in Appendix D.1) with the sentence and its full abstract.

      sentence describing how analysis was performed on data collected by the authors of this paper

  2. Sep 2024
  3. Aug 2024
    1. “Oil and gas is a connected network of processes, people, and infrastructure,” Dalgliesh says. “We are working with a client now modeling saltwater disposal wells. If you turn a valve that decreases the flow in a pipeline, it has a downstream effect on the disposal well. Knowledge graphs built on Neo4j are the perfect abstraction layer to model relationships across this kind of complex network and were a much better fit for reView than triple stores.”

      “Oil and gas is a connected network of processes, people, and infrastructure,” ... “We are working with a client now modeling saltwater disposal wells. If you turn a valve that decreases the flow in a pipeline, it has a downstream effect on the disposal well. Knowledge graphs built on Neo4j are the perfect abstraction layer to model relationships across this kind of complex network and were a much better fit for reView than triple stores.” [Jeff Dalgliesh], Chief Technology Officer at Data².

    2. “Analysts need to be able to dissect exactly how the AI reached a particular conclusion or recommendation,” says Chief Business Officer Eric Costantini. “Neo4j enables us to enforce robust information security by applying access controls at the subgraph level.”

      “Analysts need to be able to dissect exactly how the AI reached a particular conclusion or recommendation,” “Neo4j enables us to enforce robust information security by applying access controls at the subgraph level.” Chief Business Officer Eric Costantini.

  4. Jul 2023
  5. Aug 2022
    1. John Burn-Murdoch. (2021, November 25). Five quick tweets on the new variant B.1.1.529 Caveat first: Data here is very preliminary, so everything could change. Nonetheless, better safe than sorry. 1) Based on the data we have, this variant is out-competing others far faster than Beta and even Delta did 🚩🚩 https://t.co/R2Ac4e4N6s [Tweet]. @jburnmurdoch. https://twitter.com/jburnmurdoch/status/1463956686075580421

  6. Apr 2022
    1. Carl T. Bergstrom. (2021, August 18). 1. There has been lots of talk about recent data from Israel that seem to suggest a decline in vaccine efficacy against severe disease due to Delta, waning protection, or both. This may have even been a motivation for Biden’s announcement that the US would be adopting boosters. [Tweet]. @CT_Bergstrom. https://twitter.com/CT_Bergstrom/status/1427767356600688646

  7. Mar 2022
  8. Feb 2022
  9. Jan 2022
  10. Dec 2021
    1. A Marm Kilpatrick. (2021, November 24). How do we get broad immunity to SARS-CoV-2 that will protect against future variants? 2 studies (are there more?) suggest that vaccination followed by infection gives broader protection than infection followed by vaccination. @florian_krammer @profshanecrotty @GuptaR_lab https://t.co/rqdf6rE9ej [Tweet]. @DiseaseEcology. https://twitter.com/DiseaseEcology/status/1463391782742335491

    1. Tom Moultrie. (2021, December 12). Given the comedic misinterpretation of the South African testing data offered by @BallouxFrancois (and many others!) last night ... I offer some tips having contributed to the analysis of the testing data for the @nicd_sa since April last year. (1/6) [Tweet]. @tomtom_m. https://twitter.com/tomtom_m/status/1469954015932915718

    1. Art Poon. (2021, November 28). Our first https://filogeneti.ca/CoVizu update with B.1.1.529. As expected, number of mutations is well over molecular clock prediction (~13 diffs). Relatively low numbers of identical genomes implies large number of unsampled infections. We update every two days from GISAID. https://t.co/m8w2CjL1c0 [Tweet]. @art_poon. https://twitter.com/art_poon/status/1465001066194481162

    1. Eric Feigl-Ding. (2021, December 2). A rise in possible #Omicron in England—Tripling (0.1 to 0.3) of S-Gene dropout PCR signal, which is a proxy for Omicron (before 🧬 sequencing confirms). @_nickdavies estimates this represents around ~60 cases in 🏴󠁧󠁢󠁥󠁮󠁧󠁿. Still early—But it displacing #DeltaVariant is not good sign. 🧵 https://t.co/4aIiqiVsqH [Tweet]. @DrEricDing. https://twitter.com/DrEricDing/status/1466234026843205637

  11. Nov 2021
    1. Jeffrey Barrett. (2021, October 19). Proportion of AY.4.2 (now on http://covid19.sanger.ac.uk) has been steadily increasing in England, which is a pattern that is quite different from other AY lineages. Several of them rose when there was still Alpha to displace, but none has had a consistent advantage vs other Delta. Https://t.co/mD5gQzKxgV [Tweet]. @jcbarret. https://twitter.com/jcbarret/status/1450408485829718039

  12. Oct 2021
    1. Hulme, W. J., Williamson, E. J., Green, A., Bhaskaran, K., McDonald, H. I., Rentsch, C. T., Schultze, A., Tazare, J., Curtis, H. J., Walker, A. J., Tomlinson, L., Palmer, T., Horne, E., MacKenna, B., Morton, C. E., Mehrkar, A., Fisher, L., Bacon, S., Evans, D., … Goldacre, B. (2021). Comparative effectiveness of ChAdOx1 versus BNT162b2 COVID-19 vaccines in Health and Social Care workers in England: A cohort study using OpenSAFELY [Preprint]. Epidemiology. https://doi.org/10.1101/2021.10.13.21264937

  13. Sep 2021
    1. Sam Wang on Twitter: “These are risk levels that you pose to other people. They’re compared with you as—A nonsmoker—A sober driver—A vaccinated person. Unvaccinated? 5x as likely to get sick, for 3x as long. Total risk to others? 15x a vaccinated person Details:https://t.co/ckTWaivK8n https://t.co/PhpLvX2dsm” / Twitter. (n.d.). Retrieved September 19, 2021, from https://twitter.com/SamWangPhD/status/1438361144759132167

    1. Kraemer, M. U. G., Hill, V., Ruis, C., Dellicour, S., Bajaj, S., McCrone, J. T., Baele, G., Parag, K. V., Battle, A. L., Gutierrez, B., Jackson, B., Colquhoun, R., O’Toole, Á., Klein, B., Vespignani, A., COVID-19 Genomics UK (COG-UK) Consortium‡, Volz, E., Faria, N. R., Aanensen, D. M., … Pybus, O. G. (2021). Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence. Science, 373(6557), 889–895. https://doi.org/10.1126/science.abj0113

  14. Aug 2021
    1. Rogers, J. P., Watson, C. J., Badenoch, J., Cross, B., Butler, M., Song, J., Hafeez, D., Morrin, H., Rengasamy, E. R., Thomas, L., Ralovska, S., Smakowski, A., Sundaram, R. D., Hunt, C. K., Lim, M. F., Aniwattanapong, D., Singh, V., Hussain, Z., Chakraborty, S., … Rooney, A. G. (2021). Neurology and neuropsychiatry of COVID-19: A systematic review and meta-analysis of the early literature reveals frequent CNS manifestations and key emerging narratives. Journal of Neurology, Neurosurgery & Psychiatry, jnnp-2021-326405. https://doi.org/10.1136/jnnp-2021-326405

    1. Prof. Christina Pagel on Twitter: “THREAD latest on B.1.617.2 variant in England: B.1.617.2 (1st discovered in India) is now dominant in England. Here is a thread summarising latest PHE report and Sanger local data. TLDR: it is NOT good news. 1/7” / Twitter. (n.d.). Retrieved August 24, 2021, from https://twitter.com/chrischirp/status/1399333330286415876

  15. Jul 2021
    1. Leah Keating on Twitter: “This work with @DavidJPOS and @gleesonj is now on arXiv (https://t.co/hxjZnCmKcM): ‘A multi-type branching process method for modelling complex contagion on clustered networks’ Here is a quick overview of our paper: (1/6) https://t.co/3jQ2flhk71” / Twitter. (n.d.). Retrieved July 23, 2021, from https://twitter.com/leahakeating/status/1418150117106978816

  16. Jun 2021
    1. Bolze, A., Cirulli, E. T., Luo, S., White, S., Cassens, T., Jacobs, S., Nguyen, J., Ramirez, J. M., Sandoval, E., Wang, X., Wong, D., Becker, D., Laurent, M., Lu, J. T., Isaksson, M., Washington, N. L., & Lee, W. (2021). Rapid displacement of SARS-CoV-2 variant B.1.1.7 by B.1.617.2 and P.1 in the United States [Preprint]. Infectious Diseases (except HIV/AIDS). https://doi.org/10.1101/2021.06.20.21259195

  17. May 2021
    1. ReconfigBehSci on Twitter: ‘the SciBeh initiative is about bringing knowledge to policy makers and the general public, but I have to say this advert I just came across worries me: Where are the preceding data integrity and data analysis classes? Https://t.co/5LwkC1SVyF’ / Twitter. (n.d.). Retrieved 18 February 2021, from https://twitter.com/SciBeh/status/1362344945697308674

  18. Apr 2021
    1. Jeremy Faust MD MS (ER physician) on Twitter: “Let’s talk about the background risk of CVST (cerebral venous sinus thrombosis) versus in those who got J&J vaccine. We are going to focus in on women ages 20-50. We are going to compare the same time period and the same disease (CVST). DEEP DIVE🧵 KEY NUMBERS!” / Twitter. (n.d.). Retrieved April 15, 2021, from https://twitter.com/jeremyfaust/status/1382536833863651330

    1. The insertion of an algorithm’s predictions into the patient-physician relationship also introduces a third party, turning the relationship into one between the patient and the health care system. It also means significant changes in terms of a patient’s expectation of confidentiality. “Once machine-learning-based decision support is integrated into clinical care, withholding information from electronic records will become increasingly difficult, since patients whose data aren’t recorded can’t benefit from machine-learning analyses,” the authors wrote.

      There is some work being done on federated learning, where the algorithm works on decentralised data that stays in place with the patient and the ML model is brought to the patient so that their data remains private.

  19. Mar 2021
    1. Ashish K. Jha, MD, MPH. (2020, December 12). Michigan vs. Ohio State Football today postponed due to COVID But a comparison of MI vs OH on COVID is useful Why? While vaccines are coming, we have 6-8 hard weeks ahead And the big question is—Can we do anything to save lives? Lets look at MI, OH for insights Thread [Tweet]. @ashishkjha. https://twitter.com/ashishkjha/status/1337786831065264128

  20. Feb 2021
    1. Benford’s Law is a theory which states that small digits (1, 2, 3) appear at the beginning of numbers much more frequently than large digits (7, 8, 9). In theory Benford’s Law can be used to detect anomalies in accounting practices or election results, though in practice it can easily be misapplied. If you suspect a dataset has been created or modified to deceive, Benford’s Law is an excellent first test, but you should always verify your results with an expert before concluding your data has been manipulated.

      This is a relatively good explanation of Benford's law.

      I've come across the theory in advanced math, but I'm forgetting where I saw the proof. p-adic analysis perhaps? Look this up.

  21. Jan 2021
    1. Data analysis, and the parts of statistics which adhere to it, must…take on the characteristics of science rather than those of mathematics…

      Is data analysis included in data science? If not, what is the relationship between them?

  22. Dec 2020
  23. Sep 2020
  24. Aug 2020
    1. Lozano, R., Fullman, N., Mumford, J. E., Knight, M., Barthelemy, C. M., Abbafati, C., Abbastabar, H., Abd-Allah, F., Abdollahi, M., Abedi, A., Abolhassani, H., Abosetugn, A. E., Abreu, L. G., Abrigo, M. R. M., Haimed, A. K. A., Abushouk, A. I., Adabi, M., Adebayo, O. M., Adekanmbi, V., … Murray, C. J. L. (2020). Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 0(0). https://doi.org/10.1016/S0140-6736(20)30750-9

  25. Jul 2020
  26. Jun 2020
    1. Chu, D. K., Akl, E. A., Duda, S., Solo, K., Yaacoub, S., Schünemann, H. J., Chu, D. K., Akl, E. A., El-harakeh, A., Bognanni, A., Lotfi, T., Loeb, M., Hajizadeh, A., Bak, A., Izcovich, A., Cuello-Garcia, C. A., Chen, C., Harris, D. J., Borowiack, E., … Schünemann, H. J. (2020). Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: A systematic review and meta-analysis. The Lancet, 0(0). https://doi.org/10.1016/S0140-6736(20)31142-9