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Neptune: an environment for the delivery of genomic medicine
Eric Venner, Victoria Yi, David R. Murdock, Sara E. Kalla, Tsung-Jung Wu, Aniko Sabo, Shoudong Li, Qingchang Meng, Tian Xia, Mullai Murugan, Michelle Cohen, Christie Kovar, Wei‐Qi Wei, Wendy K. Chung, Chunhua Weng, Georgia L. Wiesner, Gail P. Jarvik, Donna M. Muzny, Richard A. Gibbs, Debra Abrams, Samuel E. Adunyah, Ladia Albertson‐Junkans, Berta Almoguera, Darren C. Ames, Paul S. Appelbaum, Samuel Aronson, Sharon Aufox, Lawrence Babb, Adithya Balasubramanian, Hana Bangash, Melissa Basford, Lisa Bastarache, Samantha Baxter, Meckenzie Behr, Barbara Benoit, Elizabeth Bhoj, Suzette J. Bielinski, Harris T. Bland, Carrie L. Blout Zawatsky, Kenneth M. Borthwick, Erwin P. Böttinger, Mark Bowser, Harrison Brand, Murray H. Brilliant, Wendy Brodeur, Pedro J. Caraballo, David Carrell, Andrew Carroll, Lisa Castillo, Víctor M. Castro, Gauthami Chandanavelli, Theodore Chiang, Rex L. Chisholm, Kurt D. Christensen, Christopher G. Chute, Brittany City, Beth L. Cobb, John J. Connolly, Paul K. Crane, Katherine D. Crew, David R. Crosslin, Jyoti G. Dayal, Mariza de Andrade, Jessica De la Cruz, Joshua C. Denny, Shawn Denson, Tim DeSmet, Ozan Dikilitas, Michael J. Dinsmore, Sheila Dodge, Phil Dunlea, Todd L. Edwards, Christine M. Eng, David Fasel, Alex Fedotov, QiPing Feng, Mark Fleharty, Andrea L. Foster, Robert R. Freimuth, Christopher A. Friedrich, Stephanie M. Fullerton, Birgit Funke, Stacey Gabriel, Vivian S. Gainer, Ali G. Gharavi, Andrew M. Glazer, Joseph Glessner, Jessica Goehringer, Allan Gordon, Chet Graham, Robert C. Green, Justin H. Gundelach, Heather S. Hain, Håkon Håkonarson, Maegan Harden, John B. Harley, Margaret Harr, Andrea L. Hartzler, M. Geoffrey Hayes, Scott J. Hebbring, Nora B. Henrikson, Andrew D. Hershey, Christin Hoell, Ingrid A. Holm, Kayla M. Howell, George Hripcsak, Jianhong Hu, Elizabeth Hynes, Gail P. Jarvik, Joy C. Jayaseelan, Yunyun Jiang, Yoonjung Yoonie Joo, Sheethal Jose, Navya Shilpa Josyula, Anne E. Justice, Divya Kalra, Elizabeth W. Karlson, Brendan J. Keating, Melissa Kelly, Eimear E. Kenny, Dustin Key, Krzysztof Kiryluk, Terrie Kitchner, Barbara J. Klanderman, Eric W. Klee, David C. Kochan, Viktoriya Korchina, Leah C. Kottyan, Emily Kudalkar, Alanna Kulchak Rahm, Iftikhar J. Kullo, Philip E. Lammers, Eric B. Larson, Matthew S. Lebo, Magalie S. Leduc, Ming Ta Lee, Niall J. Lennon, Kathleen A. Leppig, Nancy D. Leslie, Rongling Li, Wayne H. Liang, Chiao‐Feng Lin, Jodell E. Linder, Noralane M. Lindor, Todd Lingren, James G. Linneman, Cong Liu, Xiuping Liu, John Lynch, Hayley Lyon, Alyssa Macbeth, Harshad S. Mahadeshwar, Lisa Mahanta, Bradley Malin, Teri A. Manolio, Maddalena Marasà, Keith Marsolo, Michelle L. McGowan, Elizabeth M. McNally, Jim Meldrim, Frank Mentch, Hila Milo Rasouly, Jonathan D. Mosley, Shubhabrata Mukherjee, Thomas E. Mullen, Jesse Muniz, Shawn N. Murphy, Melanie F. Myers, Bahram Namjou, Yizhao Ni, Robert C. Onofrio, Aniwaa Owusu Obeng, Thomas N. Person, Josh F. Peterson, Lynn Petukhova, Cassandra J. Pisieczko, Siddharth Pratap, Cynthia A. Prows, Megan J. Puckelwartz, Ritika Raj, James D. Ralston, Arvind Ramaprasan, Andrea H. Ramirez, Luke V. Rasmussen, Laura J. Rasmussen‐Torvik, Soumya Raychaudhuri, Heidi L. Rehm, Marylyn D. Ritchie, Catherine Rives, Beenish Riza, Dan M. Roden, Elisabeth A. Rosenthal, Avni Santani, S Soare Dan, Steven E. Scherer, Stuart A. Scott, Aaron Scrol, Soumitra SenGupta, Ning Shang, Himanshu Sharma, Richard R. Sharp, Rajbir Singh, Patrick Sleiman, Kara Slowik, Joshua Smith, Maureen E. Smith, Duane T. Smoot, Jordan W. Smoller, Sunghwan Sohn, Ian B. Stanaway, Justin Starren, Mary Stroud, Jessica Lasky‐Su, Casey Overby Taylor, Kasia Tolwinski, Sara L. Van Driest, Sean Vargas, Matthew Varugheese, David L. Veenstra, Miguel Verbitsky, Gina Vicente, Michael Wagner, Kimberly Walker, Theresa L. Walunas, Liwen Wang, Qiaoyan Wang, Scott T. Weiss, Quinn S. Wells, Peter S. White, Ken Wiley, Janet L. Williams, Marc S. Williams, Michael W. Wilson, Leora Witkowski, Laura Woods, Betty Woolf, Julia Wynn, Yaping Yang, Ge Zhang, Lan Zhang, Hana Zouk
Bibliographic record
VenueGenetics in Medicine · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsMcGill University
FundersNational Center for Advancing Translational SciencesNational Human Genome Research InstituteBroad InstituteChildren's Hospital of PhiladelphiaVanderbilt University Medical CenterUniversity of WashingtonNational Institutes of HealthCincinnati Children's Hospital Medical CenterBrigham and Women's HospitalKaiser PermanenteNorthwestern UniversityVanderbilt University
KeywordsWorkflowNeptunePrecision medicineGenomicsPersonalized medicinePersonalizationData sciencePharmacogenomicsComputer scienceBioinformaticsComputational biologyWorld Wide WebBiologyGenomeGeneticsDatabaseGenePlanet
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)0.007
metaresearch head score (Gemma)0.020
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.093
Threshold uncertainty score0.312
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.093 | 0.033 |
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 head0.019
GPT teacher head0.269
Teacher spread0.250 · 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 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
Citations8
Published2021
Admission routes1
Has abstractno