Western News—Nearly 40,000 kids in the U.S. who lost a parent to COVID-19 need immediate support. (2021, April 5). Western News. https://news.westernu.ca/2021/04/covid-19-parent-loss/

How is it that https://en.wikipedia.org/wiki/Type_theory links to https://en.wikipedia.org/wiki/Type_(model_theory) but the latter does not have any link to or mention of https://en.wikipedia.org/wiki/Type_theory

Neither mentions the relationship between them, but both of them should, since I expect that is a common question.

Jones, M. I., Sirianni, A. D., & Fu, F. (2021). Polarization, Abstention, and the Median Voter Theorem. ArXiv:2103.12847 [Physics]. http://arxiv.org/abs/2103.12847

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Machine learning models for diagnosing COVID-19 are not yet suitable for clinical use. (2021, March 15). University of Cambridge. https://www.cam.ac.uk/research/news/machine-learning-models-for-diagnosing-covid-19-are-not-yet-suitable-for-clinical-use

Oraby, T., Thampi, V., & Bauch, C. T. (2014). The influence of social norms on the dynamics of vaccinating behaviour for paediatric infectious diseases. Proceedings of the Royal Society B: Biological Sciences, 281(1780). https://doi.org/10.1098/rspb.2013.3172

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Larremore, D. B., Wilder, B., Lester, E., Shehata, S., Burke, J. M., Hay, J. A., Tambe, M., Mina, M. J., & Parker, R. (2020). Test sensitivity is secondary to frequency and turnaround time for COVID-19 surveillance. MedRxiv, 2020.06.22.20136309. https://doi.org/10.1101/2020.06.22.20136309

Forecasting for COVID-19 has failed. (2020, June 14). International Institute of Forecasters. https://forecasters.org/blog/2020/06/14/forecasting-for-covid-19-has-failed/

COVID-19 Infections Tracker. (n.d.). COVID-19 Projections Using Machine Learning. Retrieved June 20, 2020, from https://covid19-projections.com/infections-tracker/

Silverman, J. D., Hupert, N., & Washburne, A. D. (2020). Using influenza surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United States. Science Translational Medicine. https://doi.org/10.1126/scitranslmed.abc1126

Metcalf, C. J. E., Morris, D. H., & Park, S. W. (2020). Mathematical models to guide pandemic response. Science, 369(6502), 368–369. https://doi.org/10.1126/science.abd1668

Baker, C. M., Campbell, P. T., Chades, I., Dean, A. J., Hester, S. M., Holden, M. H., McCaw, J. M., McVernon, J., Moss, R., Shearer, F. M., & Possingham, H. P. (2020). From climate change to pandemics: Decision science can help scientists have impact. ArXiv:2007.13261 [Physics]. http://arxiv.org/abs/2007.13261

Dehning, J., Zierenberg, J., Spitzner, F. P., Wibral, M., Neto, J. P., Wilczek, M., & Priesemann, V. (2020). Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions. Science. https://doi.org/10.1126/science.abb9789

Di Lauro, F., Berthouze, L., Dorey, M. D., Miller, J. C., & Kiss, I. Z. (2020). The impact of network properties and mixing on control measures and disease-induced herd immunity in epidemic models: A mean-field model perspective. ArXiv:2007.06975 [Physics, q-Bio]. http://arxiv.org/abs/2007.06975

Bertana, A., Chetverikov, A., Bergen, R. S. van, Ling, S., & Jehee, J. F. M. (2020). Dual strategies in human confidence judgments. BioRxiv, 2020.09.17.299743. https://doi.org/10.1101/2020.09.17.299743

Cheng, C., Barceló, J., Hartnett, A. S., Kubinec, R., & Messerschmidt, L. (2020). COVID-19 Government Response Event Dataset (CoronaNet v.1.0). Nature Human Behaviour, 1–13. https://doi.org/10.1038/s41562-020-0909-7

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Holme, P. (2021). Fast and principled simulations of the SIR model on temporal networks. PLOS ONE, 16(2), e0246961. https://doi.org/10.1371/journal.pone.0246961

Cantwell, G. T., Kirkley, A., & Newman, M. E. J. (2020). The friendship paradox in real and model networks. ArXiv:2012.03991 [Physics]. http://arxiv.org/abs/2012.03991

Gupta, R. K., Marks, M., Samuels, T. H. A., Luintel, A., Rampling, T., Chowdhury, H., Quartagno, M., Nair, A., Lipman, M., Abubakar, I., Smeden, M. van, Wong, W. K., Williams, B., & Noursadeghi, M. (2020). Systematic evaluation and external validation of 22 prognostic models among hospitalised adults with COVID-19: An observational cohort study. MedRxiv, 2020.07.24.20149815. https://doi.org/10.1101/2020.07.24.20149815

no

Haug, N., Geyrhofer, L., Londei, A., Dervic, E., Desvars-Larrive, A., Loreto, V., Pinior, B., Thurner, S., & Klimek, P. (2020). Ranking the effectiveness of worldwide COVID-19 government interventions. Nature Human Behaviour, 4(12), 1303–1312. https://doi.org/10.1038/s41562-020-01009-0

McKenna, S. (n.d.). COVID Models Show How to Avoid Future Lockdowns. Scientific American. Retrieved 26 February 2021, from https://www.scientificamerican.com/article/covid-models-show-how-to-avoid-future-lockdowns/

Aletti, G., Crimaldi, I., & Saracco, F. (2020). A model for the Twitter sentiment curve. ArXiv:2011.05933 [Physics]. http://arxiv.org/abs/2011.05933

Smaldino, Paul E., and Cailin O’Connor. ‘Interdisciplinarity Can Aid the Spread of Better Methods Between Scientific Communities’. MetaArXiv, 5 November 2020. https://doi.org/10.31222/osf.io/cm5v3.

Wang, X., Sirianni, A. D., Tang, S., Zheng, Z., & Fu, F. (2020). Public Discourse and Social Network Echo Chambers Driven by Socio-Cognitive Biases. Physical Review X, 10(4), 041042. https://doi.org/10.1103/PhysRevX.10.041042

Ye, Y., Zhang, Q., Ruan, Z., Cao, Z., Xuan, Q., & Zeng, D. D. (2020). Effect of heterogeneous risk perception on information diffusion, behavior change, and disease transmission. Physical Review E, 102(4), 042314. https://doi.org/10.1103/PhysRevE.102.042314

Anderson, S. C., Edwards, A. M., Yerlanov, M., Mulberry, N., Stockdale, J. E., Iyaniwura, S. A., Falcao, R. C., Otterstatter, M. C., Irvine, M. A., Janjua, N. Z., Coombs, D., & Colijn, C. (2020). Quantifying the impact of COVID-19 control measures using a Bayesian model of physical distancing. PLOS Computational Biology, 16(12), e1008274. https://doi.org/10.1371/journal.pcbi.1008274

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Hickok, A., Kureh, Y., Brooks, H. Z., Feng, M., & Porter, M. A. (2021). A Bounded-Confidence Model of Opinion Dynamics on Hypergraphs. ArXiv:2102.06825 [Nlin, Physics:Physics]. http://arxiv.org/abs/2102.06825

Aminpour, P., Gray, S. A., Singer, A., Scyphers, S. B., Jetter, A. J., Jordan, R., Murphy, R., & Grabowski, J. H. (2021). The diversity bonus in pooling local knowledge about complex problems. Proceedings of the National Academy of Sciences, 118(5). https://doi.org/10.1073/pnas.2016887118

Tepper, S., & Neil Lewis, J. (2021). When the Going Gets Tough, How Do We Perceive the Future? PsyArXiv. https://doi.org/10.31234/osf.io/pkaxn

Study shows vaccine nationalism could cost rich countries US$4.5 trillion. (2021, January 25). ICC - International Chamber of Commerce. https://iccwbo.org/media-wall/news-speeches/study-shows-vaccine-nationalism-could-cost-rich-countries-us4-5-trillion/

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Donsimoni. J. R., Glawion. R., Plachter. B., Walde. K., (2020). Projecting the Spread of COVID-19 for Germany. Institute of labor economics. Retrieved from: https://covid-19.iza.org/publications/dp13094/

gambar model yang sederhana. akan bagus kalau kita dapat menggambarkan sendiri (walaupun hanya dengan tangan) interaksi yang sama di daerah kita.

Fogg Behavior Model says that for a Behavior (B) to occur 3 things have to be present at the same time:

1. Motivation (M)
2. Ability (A)
3. Trigger (T)

B = MAT

Rocca, R., & Yarkoni, T. (2020). Putting psychology to the test: Rethinking model evaluation through benchmarking and prediction. PsyArXiv. https://doi.org/10.31234/osf.io/e437b

Soderberg, C. K., Errington, T., Schiavone, S. R., Bottesini, J. G., Thorn, F. S., Vazire, S., Esterling, K. M., & Nosek, B. A. (2020). Research Quality of Registered Reports Compared to the Traditional Publishing Model. MetaArXiv. https://doi.org/10.31222/osf.io/7x9vy

when using [[dbt]] the [[transformations]] are [[SQL statements]] - already something that our team knows

[[positional attribution]] works by identifying the touch points in the lifecycle, and dividing up the points across those touches.

There are four main ways to divvy up this pointing

[[question]] What are the four main ways to divvy up positional attribution]]

• [[first touch]]
• [[last touch]]
• [[fourty-twenty-fourty]]
• [[linear]]

[[1. Gather your required data sources]] - once we have data, we need to do two things [[sessionization]] - the aggregation of pageviews / etc into a session

and [[user stitching]] - when we have a user without any identifying information, and then converts - kind of like the anonymous users / signups - and trying to tie them back to a source

[[1. Gather your required data sources]]

[[How to build an attribution model]]

• [[1. Gather your required data sources]]
• [[2. Find all sessions before conversion]]
• [[3. Calculate the total sessions and the session index]]
• [[3. Allocate points]]
• [[4. Bonus Join in revenue value]]
• [[5. Bonus Join with ad spend data]]
• [[6. Ship it!]]

One of the goals of an [[attribution data model]] is to understand why someone [[converted]] to being a customer. This is impossible to do accurately, but this is where analysis comes in.

There are some [[approaches to attribution]], one of those is [[positional attribution]]

[[positional attribution]] is that we are weighting the importance of touch points - or customer interactions, based on their position within the customer lifetime.

[[transparent attribution model]]

[[flexible attribution model]]

[[cheapest attribution model]]

to build an [[attribution model]] we need the raw data - this raw data should capture the [[customer interactions]], and in our case - also partner interactions, or people working with the partner?

Wunderling, N., Krönke, J., Wohlfarth, V., Kohler, J., Heitzig, J., Staal, A., Willner, S., Winkelmann, R., & Donges, J. F. (2020). Modelling nonlinear dynamics of interacting tipping elements on complex networks: The PyCascades package. ArXiv:2011.02031 [Nlin, Physics:Physics]. http://arxiv.org/abs/2011.02031

ORWG Virtual Meeting 08/09/2020 https://www.youtube.com/playlist?list=PLOA0aRJ90NxvXtMt5Si5ukmR9LYfvDueB (n.d.)

The authors discuss the issue of community and engagement in online graduate programs. They carried out a small case study and used a Cognitive Apprenticeship Model to examine a successful program in Higher Education. They found that students feel too many online classes are just reading and writing, regurgitating rather than applying, and lack sufficient connection with the instructor and with other students, They recommend some strategies to fix that, but admit that more work is needed. 9/10

Fostering self-directed learning through strategy is discussed by Bailey et al. (2019) in chapter 1 of “Self-Directed Learning for the 21st Century: Implications for Higher Education.” The authors review the changing role of the educator and the learner based on respective self-directed teaching strategies (problem-based learning, cooperative learning, process-oriented learning) and the learner’s propensity for self-directed learning. In addition to providing principles to promote self-directed learning, the Grow and Borich models for implementing said learning were briefly reviewed. 8/10

The author, Kendra Grant, is the Director of Professional Development and Learning for Quillsoft in Toronto Canada. Grant helps business succeed in education design and support. In this article Grant discusses how quickly the learning environment has changed through technological development. Grant explores the RAT Model, which guides instructors in the "use of technology to help transform instructional practice." Grant then examines the Community of Inquiry model, which seeks to create meaningful instruction through social, cognitive and teaching presence. Grant concludes by providing general principles for creating a positive video presence.

Rating: 8/10

Grimm, V., Johnston, A. S. A., Thulke, H.-H., Forbes, V. E., & Thorbek, P. (2020). Three questions to ask before using model outputs for decision support. Nature Communications, 11(1), 4959. https://doi.org/10.1038/s41467-020-17785-2

Sia, S. F., Yan, L.-M., Chin, A. W. H., Fung, K., Choy, K.-T., Wong, A. Y. L., Kaewpreedee, P., Perera, R. A. P. M., Poon, L. L. M., Nicholls, J. M., Peiris, M., & Yen, H.-L. (2020). Pathogenesis and transmission of SARS-CoV-2 in golden hamsters. Nature, 583(7818), 834–838. https://doi.org/10.1038/s41586-020-2342-5

Karatayev, Vadim A., Madhur Anand, and Chris T. Bauch. ‘Local Lockdowns Outperform Global Lockdown on the Far Side of the COVID-19 Epidemic Curve’. Proceedings of the National Academy of Sciences 117, no. 39 (29 September 2020): 24575–80. https://doi.org/10.1073/pnas.2014385117.

Kaplan, Edward H, Dennis Wang, Mike Wang, Amyn A Malik, Alessandro Zulli, and Jordan H Peccia. ‘Aligning SARS-CoV-2 Indicators via an Epidemic Model: Application to Hospital Admissions and RNA Detection in Sewage Sludge’. Preprint. Infectious Diseases (except HIV/AIDS), 29 June 2020. https://doi.org/10.1101/2020.06.27.20141739.

Kubinec, Robert & Carvalho, Luiz & Barceló, Joan & Cheng, Cindy & Hartnett, Allison & Messerschmidt, Luca & Duba, Derek & Cottrell, Matthew Sean, 2020. "Partisanship and the Spread of COVID-19 in the United States," SocArXiv jp4wk, Center for Open Science. Retrieved from: https://ideas.repec.org/p/osf/socarx/jp4wk.html

Team, I. C.-19 F., & Hay, S. I. (2020). COVID-19 scenarios for the United States. MedRxiv, 2020.07.12.20151191. https://doi.org/10.1101/2020.07.12.20151191

Yang, Scott Cheng-Hsin, Chirag Rank, Jake Alden Whritner, Olfa Nasraoui, and Patrick Shafto. ‘Unifying Recommendation and Active Learning for Information Filtering and Recommender Systems’. Preprint. PsyArXiv, 25 August 2020. https://doi.org/10.31234/osf.io/jqa83.

mongoose.model()

When you call mongoose.model() on a schema, Mongoose compiles a model for you. The first argument is the singular name of the collection your model is for. Mongoose automatically looks for the plural, lowercased version of your model name. https://mongoosejs.com/docs/models.html#compiling

Covid-19 has decimated independent U.S. primary care practices—How should policymakers and payers respond? (2020, July 2). The BMJ. https://blogs.bmj.com/bmj/2020/07/02/covid-19-has-decimated-independent-u-s-primary-care-practices-how-should-policymakers-and-payers-respond/