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Image processing and analysis methods for the Adolescent Brain Cognitive Development Study

2019· article· en· W2966883685 on OpenAlexaff
Donald J. Hagler, SeanN. Hatton, M. Daniela Cornejo, Carolina Makowski, Damien A. Fair, Anthony Steven Dick, Matthew T. Sutherland, B. J. Casey, Deanna M. Barch, Michael P. Harms, Richard Watts, James M. Bjork, Hugh Garavan, Laura Hilmer, Christopher J. Pung, Chelsea S. Sicat, Joshua Kuperman, Hauke Bartsch, Feng Xue, Mary M. Heitzeg, Angela R. Laird, Thanh T. Trinh, Raúl González, Susan F. Tapert, Michael C. Riedel, Lindsay M. Squeglia, Luke W. Hyde, Monica D. Rosenberg, Eric Earl, Katia Delrahim Howlett, Fiona C. Baker, Mary Soules, Jazmín Díaz, Octavio Ruiz de Leon, Wesley K. Thompson, Michael C. Neale, Megan M. Herting, Elizabeth R. Sowell, Ruben P. Alvarez, Samuel W. Hawes, Mariana Sánchez, Jerzy Bodurka, Florence J. Breslin, Amanda Sheffield Morris, Martin P. Paulus, W. Kyle Simmons, Jon̈athan R. Polimeni, André van der Kouwe, Andrew S. Nencka, Kevin M. Gray, Carlo Pierpaoli, John A. Matochik, Antonio Noronha, Will M. Aklin, Kevin P. Conway, Meyer D. Glantz, Elizabeth A. Hoffman, Marsha F. Lopez, Vani Pariyadath, Susan R.B. Weiss, Dana L. Wolff‐Hughes, Rebecca DelCarmen‐Wiggins, Sarah W. Feldstein Ewing, Óscar Miranda-Domínguez, Bonnie J. Nagel, Anders Perrone, Darrick Sturgeon, Aimée Goldstone, Adolf Pfefferbaum, Kilian M. Pohl, Devin Prouty, Kristina A. Uban, Susan Y. Bookheimer, Mirella Dapretto, Adriana Galván, Kara Bagot, Jay N. Giedd, M. Alejandra Infante, Joanna Jacobus, Kevin Patrick, Paul D. Shilling, Rahul S. Desikan, Yi Li, Leo P. Sugrue, Marie T. Banich, Naomi P. Friedman, John K. Hewitt, Christian J. Hopfer, Joseph T. Sakai, Jody Tanabe, Linda B. Cottler, Sara Jo Nixon, Linda Chang, Christine Cloak, Thomas Ernst, Gloria Reeves, David N. Kennedy, Steve Heeringa, Scott Peltier, John E. Schulenberg, Chandra Sripada, Robert A. Zucker, William G. Iacono, Mónica Luciana, Finnegan J. Calabro, Duncan B. Clark, David A. Lewis, Beatríz Luna, Claudiu Schirda, Tufikameni Brima, John J. Foxe, Edward G. Freedman, Daniel W. Mruzek, Michael J. Mason, Rebekah S. Huber, Erin McGlade, Andrew P. Prescot, Perry F. Renshaw, Deborah Yurgelun‐Todd, Nicholas Allgaier, Julie A. Dumas, Masha Y. Ivanova, Alexandra Potter, Paul Florsheim, Christine L. Larson, Krista M. Lisdahl, Michael E. Charness, Bernard F. Fuemmeler, John M. Hettema, Hermine H. Maes, Joel L. Steinberg, Andrey P. Anokhin, Paul E.A. Glaser, Andrew C. Heath, Pamela A. F. Madden, Arielle Baskin–Sommers, R. Todd Constable, Steven Grant, Gayathri J. Dowling, Sandra A. Brown, Terry L. Jernigan, Anders M. Dale

Bibliographic record

VenueNeuroImage · 2019
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsWomen's Health Research InstituteMcGill University
FundersNational Center for Advancing Translational SciencesEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Drug AbuseNational Institute of Mental HealthNational Institute of Biomedical Imaging and BioengineeringGE HealthcareUniversity of California, San DiegoU.S. Department of Health and Human ServicesNational Institutes of HealthNational Institute on AgingNational Institute on Alcohol Abuse and Alcoholism
KeywordsNeuroimagingCognitionPsychologyFunctional magnetic resonance imagingNormativeResting state fMRINeuroscience

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.069
GPT teacher head0.376
Teacher spread0.307 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
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

Citations1,150
Published2019
Admission routes1
Has abstractno

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