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Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Behavioral Phenotyping
Aleksandra Yakhkind, Naomi Niznick, Yelena G. Bodien, Flora M. Hammond, Douglas I. Katz, Jacques Luauté, Molly McNett, Lionel Naccache, Katherine O’Brien, Caroline Schnakers, Tarek Sharshar, Beth S. Slomine, Joseph T. Giacino, Venkatesh Aiyagari, Yama Akbari, Fawaz Al‐Mufti, Sheila Alexander, Anne W. Alexandrov, Ayham Alkhachroum, Moshagan Amiri, Brian Appavu, Meron Awraris Gebre, Mary Kay Bader, Ram Balu, Megan E. Barra, Rachel Beekman, Ettore Beghi, Kathleen Bell, Tracey Berlin, Thomas P. Bleck, Varina L. Boerwinkle, Mélanie Boly, Alexandra Bonnel, Emery N. Brown, Eder Cáceres, Elizabeth Carroll, Emilio G. Cediel, Sherry Chou, Giuseppe Citerio, Jan Claassen, Chad Condie, Katie Cosmas, Claire J. Creutzfeldt, Neha Dangayach, Michael DeGeorgia, Caroline Der‐Nigoghossian, Masoom Desai, Michael N. Diringer, James Dullaway, Brian L. Edlow, Anna Estraneo, Guido J. Falcone, Salia Farrokh, Simona Ferioli, Davinia Fernández‐Espejo, Ericka L. Fink, Joseph J. Fins, Jennifer Frontera, Rishi Ganesan, Ahmeneh Ghavam, Christie Gibbons, Emily J. Gilmore, Olivia Gosseries, Theresa Green, David M. Greer, Mary Guanci, Cecil D. Hahn, Ryan Hakimi, Daniel F. Hanley, Jed A. Hartings, Ahmed M. Hassan, Raimund Helbok, Claude Hemphill, Holly E. Hinson, Karen G. Hirsch, Sarah Hocker, Theresa Human, David Hwang, Judy Illes, Matthew Jaffa, Michael L. James, Anna Janas, Morgan Jones, E. Keller, Maggie Keogh, Jenn Kim, Keri S. Kim, Hannah Kirsch, Matt Kirschen, Nerissa Ko, Daniel Kondziella, Natalie Kreitzer, Julie Kromm, Abhay Kumar, Pedro Kurtz, Steven Laureys, Thomas Lawson, Nicolas Lejeune, Ariane Lewis, John Liang, Geoffrey Ling, Sarah Livesay, Andrea I. Luppi, Lori Madden, Craig Maddux, Dea Mahanes, Shraddha Mainali, Nelson Maldonado, Rennan Martins Ribeiro, Marcello Massimini, Stephan A. Mayer, Victoria McCredie, Jorge Mejía-Mantilla, David Menon, Julio Mijangos, Asma Moheet, Erika Molteni, Martin M. Monti, Chris Morrison, Susanne Muehlschlegel, Brooke Murtaugh, Masao Nagayama, Emerson Nairon, Girija Natarajan, Virginia Newcombe, Niklas Nielsen, Filipa Noronha-Falcão, Paul Nyquist, DaiWai M. Olson, Marwan Othman, Adrian Owen, Llewellyn Padayachy, Melissa Pergakis, Len Polizzotto, Nader Pouratian, Marilyn Price Spivack, Lara Prisco, J. Javier Provencio, Louis Puybasset, Chethan Rao, Lindsay Rasmussen, Verena Rass, Michael Reznik, Risa Richardson, Cássia Righy Shinotsuka, Courtney Robertson, Benjamin Rohaut, John D. Rolston, Mario Rosanova, Mary E. Russell, Gisele Sampaio Silva, Leandro Sanz, Simone Sarasso, Aarti Sarwal, Nicolas Schiff, David B. Seder, Vishank Shah, Amy Shapiro-Rosen, Angela Hays Shapshak, Kartavya Sharma, Lori Shutter, Jacobo Sitt, Wade S. Smith, Emmanuel A. Stamatakis, Alexis Steinberg, Robert D. Stevens, José I. Suarez, Bethany L. Sussman, Shaurya Taran, Aurore Thibaut, Zachary Threlkeld, Lorenzo Tinti, Daniel Toker, Michel Torbey, Stephen Trevick, Alexis F. Turgeon, Andrew Udy, Panos Varelas, Paul Vespa, Walter Videtta, Henning U. Voss, Ford Vox, Amy K. Wagner, John Whyte, Briana Witherspoon, Aleksandra Yakhind, Ross Zafonte, Darin B. Zahuranec, Chris Zammit, Bei Zhang, Wendy Ziai, Lara Zimmerman, Elizabeth Zink
Bibliographic record
VenueNeurocritical Care · 2023
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsOttawa Hospital
FundersNational Institute on Disability, Independent Living, and Rehabilitation ResearchU.S. Department of Defense
KeywordsMedicineNeurointensive carePersistent vegetative stateTerminologyNeuroimagingNeurologyIntensive care medicinePsychiatryConsciousnessMinimally conscious stateNeurosciencePsychology
Abstract
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 imitationNot 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)0.264
metaresearch head score (Gemma)0.505
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.736
Threshold uncertainty score0.908
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.264 | 0.505 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.016 |
| Bibliometrics | 0.026 | 0.017 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.016 | 0.019 |
| Open science | 0.017 | 0.016 |
| Research integrity | 0.018 | 0.028 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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 head0.223
GPT teacher head0.444
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
Study designNot applicable
DomainMethods
GenreMethods
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations21
Published2023
Admission routes1
Has abstractno