Record W3194359278 · doi:10.1038/s41592-022-01415-4

MITI minimum information guidelines for highly multiplexed tissue images

2022· article· en· W3194359278 on OpenAlexfundno aff

Denis Schapiro, Clarence Yapp, Artem Sokolov, Sheila M. Reynolds, Damir Sudar, Yubin Xie, Jeremy L. Muhlich, Raquel Arias-Camison, Sarah Arena, Adam Taylor, Milen Nikolov, Madison Tyler, Jia‐Ren Lin, Erik Burlingame, Daniel L. Abravanel, Samuel Achilefu, Foluso O. Ademuyiwa, Andrew Adey, Rebecca Aft, Khung Jun Ahn, Fatemeh Alikarami‬, Shahar Alon, Orr Ashenberg, Ethan Baker, Gregory J. Baker, Shovik Bandyopadhyay, Peter O. Bayguinov, Jennifer Beane, Winston R. Becker, Kathrin M. Bernt, Courtney B. Betts, Julie Bletz, Tim Blosser, Adrienne Boire, Genevieve M. Boland, Edward S. Boyden, Elmar Bucher, Raphael Bueno, Qiuyin Cai, Francesco Cambuli, Joshua D. Campbell, Song Cao, Wagma Caravan, Ronan Chaligné, Joseph M. Chan, Sara E. Chasnoff, Deyali Chatterjee, Alyce A. Chen, Changya Chen, Chia‐Hui Chen, Bob Chen, Feng Chen, Siqi Chen, Milan G. Chheda, Koei Chin, Hyeyoung Cho, Jaeyoung Chun, Luis Cisneros, Robert J. Coffey, Ofir Cohen, Graham A. Colditz, Kristina A. Cole, Natalie B. Collins, Daniel J. Cotter, Lisa M. Coussens, Shannon Coy, Allison Creason, Yi Cui, Daniel Cui Zhou, Christina Curtis, Sherri R. Davies, Ino de Bruijn, Toni Delorey, Emek Demir, David G. DeNardo, Dinh Diep, Li Ding, John F. DiPersio, Steven M. Dubinett, Timothy J. Eberlein, James A. Eddy, Edward D. Esplin, Rachel E. Factor, Kayvon Fatahalian, Heidi S. Feiler, José M. Fernández, Andrew J. Fields, Ryan C. Fields, James A. J. Fitzpatrick, James M. Ford, Jeff Franklin, Bob Fulton, Giorgio Gaglia, Luciano Galdieri, Karuna Ganesh, Jianjiong Gao, Benjamin L. Gaudio, Gad Getz, David L. Gibbs, William E. Gillanders, Jeremy Goecks, Daniel Goodwin, Joe W. Gray, William J. Greenleaf, Lars J. Grimm, Qiang Gu, Jennifer L. Guerriero, Tuhin K. Guha, Alexander R. Guimarães, Belén Gutiérrez‐Gutiérrez, Nir Hacohen, Casey Ryan Hanson, Coleman R. Harris, William G. Hawkins, Cody N. Heiser, John Hoffer, Travis J. Hollmann, James J. Hsieh, Jeffrey Huang, Stephen P. Hunger, Eun-Sil Shelley Hwang, Christine A. Iacobuzio–Donahue, Michael D. Iglesia, Mohammad Hayatul Islam, Benjamin Izar, Connor A. Jacobson, Sam M. Janes, Reyka G. Jayasinghe, Tiarah Jeudi, Bruce E. Johnson, Brett Johnson, Tao Ju, Humam Kadara, Elias-Ramzey Karnoub, Alla Y. Karpova, Aziz Khan, Warren A. Kibbe, Albert H. Kim, Lorraine King, Elyse Kozlowski, Praveen Krishnamoorthy, Robert Krueger, Anshul Kundaje, Uri Ladabaum, Rozelle Laquindanum, Clarisse Lau, Ken S. Lau, Nicole R. LeBoeuf, Hayan Lee, Marc E. Lenburg, Ignaty Leshchiner, Rochelle Levy, Yize Li, Christine G. Lian, Wen-Wen Liang, Kian‐Huat Lim, Yiyun Lin, David Liu, Qi Liu, Ruiyang Liu, Joseph Y. Lo, Pierrette Lo, William J.R. Longabaugh, Teri A. Longacre, Katie Luckett, X. Cynthia, Christopher G. Maher, Allison Maier, Danika Makowski, Carlo C. Maley, Zoltan Maliga, Parvathy Manoj, John M. Maris, Nick Markham, Jeffrey R. Marks, Daniel Martínez, Jay R. Mashl, Ignas Masilionis, Joan Massagué, Marciej A. Mazurowski, Eliot T. McKinley, Joshua F. McMichael, Matthew Meyerson, Gordon B. Mills, Zahi Mitri, Andrew Moorman, Jacqueline L. Mudd, Gëorge F. Murphy, Nataly Naser Al Deen, Nicholas E. Navin, Tal Nawy, Reid M. Ness, Stephanie Nevins, Ajit J. Nirmal, Edward Novikov, Stephen T. Oh, Derek A. Oldridge, Kouros Owzar, Shishir M. Pant, Wungki Park, Gary J. Patti, Kristina Paul, Roxanne J. Pelletier, Daniel Persson, Candi Petty, Hanspeter Pfister, Kornélia Polyák, Sidharth V. Puram, Qi Qiu, Álvaro Quintanal Villalonga, Marisol Ramirez, Rumana Rashid, Ashley N. Reeb, Mary E. Reid, Ján Remšík, Jessica L. Riesterer, Tyler Risom, Cecily C. Ritch, Andrea Rolong, Charles M. Rudin, Marc D. Ryser, Kazuhito Sato, Cynthia L. Sears, Yevgeniy R. Semenov, Jeanne Shen, Kooresh I. Shoghi, Martha J. Shrubsole, Yu Shyr, Alexander B. Sibley, Alan J. Simmons, Anubhav Sinha, Shamilene Sivagnanam, Sheng-Kwei Song, Austin Southar-Smith, Avrum Spira, Jeremy St. Cyr, Stephanie Stefankiewicz, Erik Storrs, Elizabeth H. Stover, Siri H. Strand, Cody Straub, Cherease Street, Timothy Su, Lea F. Surrey, Christine Suver, Kai Tan, Nadezhda V. Terekhanova, Luke Ternes, Anusha Thadi, George Thomas, Rob Tibshirani, Shigeaki Umeda, Yasin Uzun, Tuulia Vallius, Eliezer R. Van Allen, Simon Vandekar, Paige N. Vega, Deborah J. Veis, Sujay Vennam, Ana Verma, Sébastien Vigneau, Nikhil Wagle, Richard Wahl, Thomas Walle, Liang-Bo Wang, Simon Warchol, M. Kay Washington, Cameron Watson, Annika K. Weimer, Michael C. Wendl, Robert B. West, Shannon White, Annika Windon, Hao Wu, Chi-Yun Wu, Yige Wu, Matthew A. Wyczalkowski, Jason Xu, Lijun Yao, Wenbao Yu, Kun Zhang, Xiangzhu Zhu, Young Hwan Chang, Samouil L. Farhi, Vésteinn Thórsson, Nithya Venkatamohan, Julia L. Drewes, Dana Pe’er, David A. Gutman, Markus D. Herrmann, Nils Gehlenborg, Peter Bankhead, Joseph T. Roland, John M. Herndon, M Snyder, Michael Angelo, Garry P. Nolan, Jason R. Swedlow, Nikolaus Schultz, Daniel T. Merrick, Sarah A. Mazzili, Ethan Cerami, Scott J. Rodig, Sandro Santagata, Peter K. Sorger

Bibliographic record

VenueNature Methods · 2022

Typearticle

Languageen

FieldBiochemistry, Genetics and Molecular Biology

TopicSingle-cell and spatial transcriptomics

Canadian institutionsnot available

FundersInstitute of GeneticsNational Cancer InstituteNational Human Genome Research InstituteLudwig Center at HarvardDana-Farber Cancer InstituteSchool of Medicine, Vanderbilt UniversitySchool of Medicine, Stanford UniversityUniversitätsklinikum HeidelbergMemorial Sloan-Kettering Cancer CenterJohns Hopkins UniversityBroad InstituteVanderbilt University Medical CenterOregon Health and Science UniversityVanderbilt UniversityDamon Runyon Cancer Research FoundationChildren's Hospital of PhiladelphiaSchool of Medicine, Emory UniversityBundesministerium für Bildung und ForschungDepartment of Systems Biology, Harvard Medical SchoolNational Science FoundationMassachusetts General HospitalBrigham and Women's HospitalEmory UniversityKlarman Cell Observatory, Broad InstituteUniversity of DundeeNational Institutes of HealthSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungU.S. Department of Health and Human Services

KeywordsMetadataMultiplexingComputer scienceMicroscopyGenomicsComputational biologyBiologyGenomePathologyWorld Wide WebMedicineGeneGenetics

DOI10.1038/s41592-022-01415-4

Abstract

fetched live from OpenAlex

No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008

metaresearch head score (Gemma)0.021

Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated

Candidate categoriesMetaresearch

Consensus categoriesnone

DomainCandidate signal: Reporting · Consensus signal: none

Study designCandidate signal: Not applicable · Consensus signal: Not applicable

GenreCandidate signal: Methods · Consensus signal: Methods

Teacher disagreement score0.992

Threshold uncertainty score0.501

Distilled classifier scores by category (both heads)

Category	Codex	Gemma
Metaresearch	0.008	0.021
Meta-epidemiology (narrow)	0.002	0.004
Meta-epidemiology (broad)	0.002	0.002
Bibliometrics	0.006	0.003
Science and technology studies	0.002	0.001
Scholarly communication	0.003	0.003
Open science	0.006	0.004
Research integrity	0.005	0.003
Insufficient payload (model declined to judge)	0.150	0.140

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036

GPT teacher head0.392

Teacher spread0.356 · how far apart the two teachers sit on this one work

Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it