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Black Hole

Lensing of space time around a black hole. At Oxford we study black holes observationally and theoretically on all size and time scales - it is some of our core work.

Credit: ALAIN RIAZUELO, IAP/UPMC/CNRS. CLICK HERE TO VIEW MORE IMAGES.

Prof Chris Lintott

Professor of Astrophysics and Citizen Science Lead

Research theme

  • Astronomy and astrophysics

Sub department

  • Astrophysics

Research groups

  • Zooniverse
  • Beecroft Institute for Particle Astrophysics and Cosmology
  • Rubin-LSST
chris.lintott@physics.ox.ac.uk
Telephone: 01865 (2)73638
Denys Wilkinson Building, room 532C
www.zooniverse.org
orcid.org/0000-0001-5578-359X
  • About
  • Citizen science
  • Group alumni
  • Publications

Zooniverse labs

Zooniverse lab
Build your own Zooniverse project

The Zooniverse lab lets anyone build their own citizen science project

Zooniverse Lab

Galaxy Zoo: CANDELS barred discs and bar fractions★

Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) 445:4 (2014) 3466-3474

Authors:

BD Simmons, Thomas Melvin, Chris Lintott, Karen L Masters, Kyle W Willett, William C Keel, RJ Smethurst, Edmond Cheung, Robert C Nichol, Kevin Schawinski, Michael Rutkowski, Jeyhan S Kartaltepe, Eric F Bell, Kevin RV Casteels, Christopher J Conselice, Omar Almaini, Henry C Ferguson, Lucy Fortson, William Hartley, Dale Kocevski, Anton M Koekemoer, Daniel H McIntosh, Alice Mortlock, Jeffrey A Newman, Jamie Ownsworth, Steven Bamford, Tomas Dahlen, Sandra M Faber, Steven L Finkelstein, Adriano Fontana, Audrey Galametz, NA Grogin, Ruth Grützbauch, Yicheng Guo, Boris Häußler, Kian J Jek, Sugata Kaviraj, Ray A Lucas, Michael Peth, Mara Salvato, Tommy Wiklind, Stijn Wuyts
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The Solar Stormwatch CME catalogue: Results from the first space weather citizen science project

Space Weather American Geophysical Union (AGU) 12:12 (2014) 657-674

Authors:

L Barnard, C Scott, M Owens, M Lockwood, K Tucker‐Hood, S Thomas, S Crothers, JA Davies, R Harrison, C Lintott, R Simpson, J O'Donnell, AM Smith, N Waterson, S Bamford, F Romeo, M Kukula, B Owens, N Savani, J Wilkinson, E Baeten, L Poeffel, B Harder
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PLANET HUNTERS. VII. DISCOVERY OF A NEW LOW-MASS, LOW-DENSITY PLANET (PH3 C) ORBITING KEPLER-289 WITH MASS MEASUREMENTS OF TWO ADDITIONAL PLANETS (PH3 B AND D)**This publication has been made possible by the participation of more than 290,000 volunteers in the Planet Hunters project. Their contributions are individually acknowledged at http://www.planethunters.org/authors.

The Astrophysical Journal American Astronomical Society 795:2 (2014) 167

Authors:

Joseph R Schmitt, Eric Agol, Katherine M Deck, Leslie A Rogers, J Zachary Gazak, Debra A Fischer, Ji Wang, Matthew J Holman, Kian J Jek, Charles Margossian, Mark R Omohundro, Troy Winarski, John M Brewer, Matthew J Giguere, Chris Lintott, Stuart Lynn, Michael Parrish, Kevin Schawinski, Megan E Schwamb, Robert Simpson, Arfon M Smith
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A Computational Pipeline for Crowdsourced Transcriptions of Ancient Greek Papyrus Fragments

Institute of Electrical and Electronics Engineers (IEEE) (2014) 100-105

Authors:

Alex C Williams, John F Wallin, Haoyu Yu, Marco Perale, Hyrum D Carroll, Anne-Francoise Lamblin, Lucy Fortson, Dirk Obbink, Chris J Lintott, James H Brusuelas
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Crowd-sourced assessment of technical skills: A novel method to evaluate surgical performance

Journal of Surgical Research 187:1 (2014) 65-71

Authors:

C Chen, L White, T Kowalewski, R Aggarwal, C Lintott, B Comstock, K Kuksenok, C Aragon, D Holst, T Lendvay

Abstract:

Background Validated methods of objective assessments of surgical skills are resource intensive. We sought to test a web-based grading tool using crowdsourcing called Crowd-Sourced Assessment of Technical Skill. Materials and methods Institutional Review Board approval was granted to test the accuracy of Amazon.com's Mechanical Turk and Facebook crowdworkers compared with experienced surgical faculty grading a recorded dry-laboratory robotic surgical suturing performance using three performance domains from a validated assessment tool. Assessor free-text comments describing their rating rationale were used to explore a relationship between the language used by the crowd and grading accuracy. Results Of a total possible global performance score of 3-15, 10 experienced surgeons graded the suturing video at a mean score of 12.11 (95% confidence interval [CI], 11.11-13.11). Mechanical Turk and Facebook graders rated the video at mean scores of 12.21 (95% CI, 11.98-12.43) and 12.06 (95% CI, 11.57-12.55), respectively. It took 24 h to obtain responses from 501 Mechanical Turk subjects, whereas it took 24 d for 10 faculty surgeons to complete the 3-min survey. Facebook subjects (110) responded within 25 d. Language analysis indicated that crowdworkers who used negation words (i.e., "but," "although," and so forth) scored the performance more equivalently to experienced surgeons than crowdworkers who did not (P < 0.00001). Conclusions For a robotic suturing performance, we have shown that surgery-naive crowdworkers can rapidly assess skill equivalent to experienced faculty surgeons using Crowd-Sourced Assessment of Technical Skill. It remains to be seen whether crowds can discriminate different levels of skill and can accurately assess human surgery performances. © 2014 Elsevier Inc. All rights reserved.
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