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SPARK: A US Cohort of 50,000 Families to Accelerate Autism Research
Pamela Feliciano, Amy M. Daniels, LeeAnne Green Snyder, Amy L. Beaumont, Alexies Camba, Amy Esler, Amanda G. Gulsrud, Andrew Z. Mason, Anibal Gutierrez, Amy Nicholson, Anna Marie Paolicelli, Alexander P. McKenzie, Angela L. Rachubinski, Alexandra N. Stephens, Andrea R. Simon, Amy Stedman, Amanda D. Shocklee, Amy Swanson, Brenda Finucane, Brittani A. Hilscher, Brenda Hauf, Brian J. O’Roak, Brooke G. McKenna, B. E. Robertson, Bárbara Rodríguez, Brianna M. Vernoia, Bonnie Van Metre, Catherine C. Bradley, Cheryl Cohen, Craig A. Erickson, Christina Harkins, Caitlin Hayes, Catherine Lord, Crissy Ortiz, Cesar Ochoa‐Lubinoff, Christine Peura, Catherine E. Rice, Cordelia Robinson Rosenberg, Christopher J. Smith, Carrie A. Thomas, Cora Taylor, L. Casey White, Corrie H. Walston, David G. Amaral, Daniel L. Coury, Dustin E. Sarver, Dalia Istephanous, Deana Li, Dzung Cong Nugyen, Emily A. Fox, Eric Butter, Elizabeth Berry‐Kravis, Éric Fombonne, Eugenia Hofammann, Elena Lamarche, Ericka L. Wodka, Emily T. Matthews, Eirene O’Connor, Emily Palen, Fiona K. Miller, Gabriel S. Dichter, Gabriela Marzano, Gail Stein, Hanna Hutter, Hannah E. Kaplan, Hai Li, Holly Lechniak, Hoa Lam Schneider, Hana Zaydens, Ivette Arriaga, Jennifer Gerdts, Joseph F. Cubells, Jeanette M Cordova, Jaclyn Gunderson, Joseph Lillard, Julie Manoharan, James T. McCracken, Jacob J. Michaelson, Jason Neely, Jéssica Orobio, Juhi Pandey, Joseph Piven, Jessica Scherr, James S. Sutcliffe, Jennifer Tjernagel, Jermel Wallace, Kristen Callahan, Katherine Ann Dent, Kathryn A. Schweers, Kira E. Hamer, Kiely Law, Kathryn Lowe, Kaela O’Brien, Kaitlin Smith, Katherine G. Pawlowski, Karen Pierce, Katherine Roeder, Leonard Abbeduto, Leandra N. Berry, Lindsey A. Cartner, Leigh A. Coppola, Laura A. Carpenter, Lisa Cordeiro, Lindsey DeMarco, Luke P. Grosvenor, Lorrin Higgins, Lark Y. Huang-Storms, Landon Hosmer-Quint, Lynette M. Herbert, Lisa M. Prock, Lillian D. Pacheco, Laurie Raymond, Laura Simon, Latha V. Soorya, Lucy Wasserburg, Maya Lazar, Michael Alessandri, Melissa Shani Brown, Mary Hannah Currin, McLeod F. Gwynette, Michelle Heyman, Melissa N. Hale, Mark Jones, Michelle Jordy, Michael J. Morrier, Mustafa Şahin, Matthew Siegel, Mary Verdi, Meaghan V. Parladé, Meredith Yinger, Nicole Bardett, Nathan Hanna, Nina Harris, Natalie Pottschmidt, Nicole M. Russo‐Ponsaran, Nicole Takahashi, Opal Ousley, Aline Juárez, Patricia Manning, Robert D. Annett, Raphael Bernier, Renee D. Clark, Rebecca Landa, Robin P. Goin‐Kochel, Rick Remington, Robert T. Schultz, Stephanie Brewster, Stephanie Booker, Sara Eldred, Sunday M. Francis, Sandra Friedman, Susannah Horner, Susan Hepburn, Suma Jacob, Stephen M. Kanne, Soo J. Lee, Sarah Mastel, Samantha Plate, Shanping Qiu, Sophia Sandhu, Samantha Thompson, Sabrina White, Vincent J. Myers, Vini Singh, Wha S. Yang, Zachary Warren, Alpha Amatya, Ahmad S. Chatha, Alex Lash, Ben Negron, Chris Rigby, Curtis Ridenour, Colleen M. Stock, Danielle Schmidt, I. Fisk, John Acampado, Jay L. Nestle, Jay Nestle, Kevin Layman, Martin E. Butler, Matt Kent, Malcolm D. Mallardi, Nicholas Carriero, Noah Lawson, Natalia Volfovsky, Ron Edgar, Richard P. Marini, Rishiraj Rana, Swami Ganesan, Swapnil Shah, Tyler Ramsey, Wubin Chin, William Jensen, Anthony D. Krentz, Angela Gruber, Aniko Sabo, Andrei Salomatov, Christine M. Eng, Donna M. Muzny, Irina Astrovskaya, Richard A. Gibbs, Xinwei Han, Yufeng Shen, Louis F. Reichardt, Wendy K. Chung
Bibliographic record
VenueNeuron · 2018
Typereview
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
FundersNational Institute on Deafness and Other Communication DisordersNational Institute of Mental HealthSage TherapeuticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentSimons Foundation Autism Research InitiativeSimons FoundationLAM TherapeuticsDNA Genotek
KeywordsAutism spectrum disorderAutismPsychologySPARK (programming language)PsychiatryClinical psychologyMedicineComputer science
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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.041
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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 head0.221
GPT teacher head0.444
Teacher spread0.223 · 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; 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 designObservational
Domainnot available
GenreReview
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
Citations492
Published2018
Admission routes1
Has abstractno