ERRATUM: “PLANET HUNTERS. VI. AN INDEPENDENT CHARACTERIZATION OF KOI-351 AND SEVERAL LONG PERIOD PLANET CANDIDATES FROM THE KEPLER ARCHIVAL DATA” (2014, AJ, 148, 28)*

The Astronomical Journal American Astronomical Society 150:1 (2015) 38

Authors:

Joseph R Schmitt, Ji Wang, Debra A Fischer, Kian J Jek, John C Moriarty, Tabetha S Boyajian, Megan E Schwamb, Chris Lintott, Stuart Lynn, Arfon M Smith, Michael Parrish, Kevin Schawinski, Robert Simpson, Daryll LaCourse, Mark R Omohundro, Troy Winarski, Samuel Jon Goodman, Tony Jebson, Hans Martin Schwengeler, David A Paterson, Johann Sejpka, Ivan Terentev, Tom Jacobs, Nawar Alsaadi, Robert C Bailey, Tony Ginman, Pete Granado, Kristoffer Vonstad Guttormsen, Franco Mallia, Alfred L Papillon, Franco Rossi, Miguel Socolovsky, Lubomir Stiak

Euclid space mission: a cosmological challenge for the next 15 years

Proceedings of the International Astronomical Union Cambridge University Press 10:S306 (2015) 375-378

Authors:

Roberto Scaramella, Yannick Mellier, Jerome Amiaux, Carlo Burigana, C Sofia Carvalho, Jean-Charles Cuillandre, Antonio D Silva, Joao Dinis, Adriano Derosa, Elena Maiorano, Paolo Franzetti, Bianca Garilli, Michele Maris, Massimo Meneghetti, Ismael Tereno, Stefanie Wachter, Luca Amendola, Mark Cropper, Vincenzo Cardone, Robert Massey, Sami Niemi, Henk Hoekstra, Thomas Kitching, Lance Miller, Timothy Schrabback, Elisabetta Semboloni, Andrew Taylor, Massimo Viola, Thierry Maciaszek, Anne Ealet, Luigi Guzzo, Knud Jahnke, Will Percival, Fabio Pasian, Marc Sauvage

Abstract:

Euclid is the next ESA mission devoted to cosmology. It aims at observing most of the extragalactic sky, studying both gravitational lensing and clustering over $\sim$15,000 square degrees. The mission is expected to be launched in year 2020 and to last six years. The sheer amount of data of different kinds, the variety of (un)known systematic effects and the complexity of measures require efforts both in sophisticated simulations and techniques of data analysis. We review the mission main characteristics, some aspects of the the survey and highlight some of the areas of interest to this meeting

GREAT3 results – I. Systematic errors in shear estimation and the impact of real galaxy morphology

Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) 450:3 (2015) 2963-3007

Authors:

Rachel Mandelbaum, Barnaby Rowe, Robert Armstrong, Deborah Bard, Emmanuel Bertin, James Bosch, Dominique Boutigny, Frederic Courbin, William A Dawson, Annamaria Donnarumma, Ian Fenech Conti, Raphaël Gavazzi, Marc Gentile, Mandeep SS Gill, David W Hogg, Eric M Huff, M James Jee, Tomasz Kacprzak, Martin Kilbinger, Thibault Kuntzer, Dustin Lang, Wentao Luo, Marisa C March, Philip J Marshall, Joshua E Meyers, Lance Miller, Hironao Miyatake, Reiko Nakajima, Fred Maurice Ngolé Mboula, Guldariya Nurbaeva, Yuki Okura, Stéphane Paulin-Henriksson, Jason Rhodes, Michael D Schneider, Huanyuan Shan, Erin S Sheldon, Melanie Simet, Jean-Luc Starck, Florent Sureau, Malte Tewes, Kristian Zarb Adami, Jun Zhang, Joe Zuntz

STELLAR POPULATIONS OF BARRED QUIESCENT GALAXIES

The Astrophysical Journal American Astronomical Society 807:1 (2015) 36

Authors:

Edmond Cheung, Charlie Conroy, E Athanassoula, Eric F Bell, A Bosma, Carolin N Cardamone, SM Faber, David C Koo, Chris Lintott, Karen L Masters, Thomas Melvin, Brooke Simmons, Kyle W Willett

Crowdsourcing the General Public for Large Scale Molecular Pathology Studies in Cancer.

EBioMedicine 2:7 (2015) 681-689

Authors:

Francisco J Candido Dos Reis, Stuart Lynn, H Raza Ali, Diana Eccles, Andrew Hanby, Elena Provenzano, Carlos Caldas, William J Howat, Leigh-Anne McDuffus, Bin Liu, Frances Daley, Penny Coulson, Rupesh J Vyas, Leslie M Harris, Joanna M Owens, Amy FM Carton, Janette P McQuillan, Andy M Paterson, Zohra Hirji, Sarah K Christie, Amber R Holmes, Marjanka K Schmidt, Montserrat Garcia-Closas, Douglas F Easton, Manjeet K Bolla, Qin Wang, Javier Benitez, Roger L Milne, Arto Mannermaa, Fergus Couch, Peter Devilee, Robert AEM Tollenaar, Caroline Seynaeve, Angela Cox, Simon S Cross, Fiona M Blows, Joyce Sanders, Renate de Groot, Jonine Figueroa, Mark Sherman, Maartje Hooning, Hermann Brenner, Bernd Holleczek, Christa Stegmaier, Chris Lintott, Paul DP Pharoah

Abstract:

Background

Citizen science, scientific research conducted by non-specialists, has the potential to facilitate biomedical research using available large-scale data, however validating the results is challenging. The Cell Slider is a citizen science project that intends to share images from tumors with the general public, enabling them to score tumor markers independently through an internet-based interface.

Methods

From October 2012 to June 2014, 98,293 Citizen Scientists accessed the Cell Slider web page and scored 180,172 sub-images derived from images of 12,326 tissue microarray cores labeled for estrogen receptor (ER). We evaluated the accuracy of Citizen Scientist's ER classification, and the association between ER status and prognosis by comparing their test performance against trained pathologists.

Findings

The area under ROC curve was 0.95 (95% CI 0.94 to 0.96) for cancer cell identification and 0.97 (95% CI 0.96 to 0.97) for ER status. ER positive tumors scored by Citizen Scientists were associated with survival in a similar way to that scored by trained pathologists. Survival probability at 15 years were 0.78 (95% CI 0.76 to 0.80) for ER-positive and 0.72 (95% CI 0.68 to 0.77) for ER-negative tumors based on Citizen Scientists classification. Based on pathologist classification, survival probability was 0.79 (95% CI 0.77 to 0.81) for ER-positive and 0.71 (95% CI 0.67 to 0.74) for ER-negative tumors. The hazard ratio for death was 0.26 (95% CI 0.18 to 0.37) at diagnosis and became greater than one after 6.5 years of follow-up for ER scored by Citizen Scientists, and 0.24 (95% CI 0.18 to 0.33) at diagnosis increasing thereafter to one after 6.7 (95% CI 4.1 to 10.9) years of follow-up for ER scored by pathologists.

Interpretation

Crowdsourcing of the general public to classify cancer pathology data for research is viable, engages the public and provides accurate ER data. Crowdsourced classification of research data may offer a valid solution to problems of throughput requiring human input.