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Initial sequencing and comparative analysis of the mouse genome
R Waterston, Kerstin Lindblad‐Toh, Ewan Birney, Jane Rogers, Josep F. Abril, Pankaj Agarwal, Richa Agarwala, Rachel Ainscough, Marina Alexandersson, Peter An, Stylianos E. Antonarakis, Robert Baertsch, J. Bailey, K. F. Barlow, Stephan Beck, E. Berry, Bruce W. Birren, Toby Bloom, Peer Bork, Marc Botcherby, Nicolas Bray, Michael R. Brent, Daniel G. Brown, S.D.M. Brown, Carol J. Bult, John H. Burton, Jonathan A. Butler, R. Duncan Campbell, Piero Carninci, Simon Cawley, Francesca Chiaromonte, Asif Chinwalla, Deanna M. Church, Michèle Clamp, Christopher Clee, Francis S. Collins, Lisa L. Cook, Richard R. Copley, Alan Coulson, Olivier Couronne, James Cuff, Val Curwen, Tim Cutts, Mark Daly, Robert David, J. Davies, Kimberly D. Delehaunty, Justin Deri, Emmanouil T. Dermitzakis, Colin N. Dewey, Nicholas J. Dickens, Mark Diekhans, Sheila Dodge, Inna Dubchak, Diane M. Dunn, Sean R. Eddy, Laura Elnitski, Richard D. Emes, Pallavi Eswara, Eduardo Eyras, Adam L. Felsenfeld, Ginger Fewell, Paul Flicek, Karen Foley, Wayne N. Frankel, Lucinda A. Fulton, Robert S. Fulton, Terrence S. Furey, Diane Gage, Richard A. Gibbs, Gustavo Glusman, Sante Gnerre, Nick Goldman, Leo Goodstadt, Darren Grafham, Tina Graves, Eric D. Green, Simon G. Gregory, Roderic Guigó, Mark S. Guyer, Ross C. Hardison, David Haussler, Yoshihide Hayashizaki, LaDeana W. Hillier, Wratko Hlavina, Timothy R. Holzer, Fan Hsu, Axin Hua, Tim Hubbard, Adrienne Hunt, Ian J. Jackson, David B. Jaffe, L. Steven Johnson, Matthew C. Jones, Thomas A. Jones, Ann Joy, Michael Kamal, Elinor K. Karlsson, Donna Karolchik, Arkadiusz Kasprzyk, Jun Kawai, Evan Keibler, Cristyn Kells, W. James Kent, Andrew Kirby, Diana L. Kolbe, Ian Korf, Raju Kucherlapati, Edward J. Kulbokas, David Kulp, Tom Landers, J P Leger, Steven Leonard, Ivica Letunić, R Paul Levine, Jia Li, Ming Li, Christine Lloyd, Susan Lucas, Bin Ma, Donna Maglott, Elaine R. Mardis, Lucy Matthews, Evan Mauceli, John H. Mayer, Megan McCarthy, W. Richard McCombie, Stuart McLaren, Kirsten McLay, John D. McPherson, Jim Meldrim, Beverley Meredith, Jill P. Mesirov, Webb Miller, Tracie L. Miner, Emmanuel Mongin, Kate Montgomery, Michael J. Morgan, Richard Mott, James C. Mullikin, Donna M. Muzny, William E. Nash, Joanne O. Nelson, Michael N. Nhan, Robert Nicol, Zemin Ning, Chad Nusbaum, Michael J. O’Connor, Yasushi Okazaki, Karen Oliver, E. K. Overton-Larty, Lior Pachter, Genı́s Parra, Kymberlie Pepin, Jane L. Peterson, Pavel A. Pevzner, R. W. Plumb, Craig Pohl, Alex Poliakov, Tracy C Ponce, Chris P. Ponting, Simon Potter, Michael A. Quail, Alexandre Reymond, Bruce A. Roe, Krishna M. Roskin, Edward M. Rubin, Alistair G. Rust, Ralph Santos, Victor Sapojnikov, Brian Schultz, Jörg Schultz, Matthias S Schwartz, Scott Schwartz, Carol Scott, Steven Seaman, Steve Searle, Ted Sharpe, Andrew Sheridan, R. Shownkeen, Sarah Sims, Jonathan B. Singer, Guy Slater, Arian F. A. Smit, Brian Spencer, Arne Stabenau, Nicole Stange-Thomann, Charles W. Sugnet, Mikita Suyama, Glenn Tesler, J.E. Thompson, David Torrents, E. Trevaskis, John Tromp, Catherine Ucla, Abel Ureta‐Vidal, Jade P. Vinson, Andrew C. von Niederhausern, Claire M. Wade, Melanie Wall, Ryan Weber, Robert B. Weiss, Michael C. Wendl, Anthony P. West, Kris A. Wetterstrand, Raymond M. Wheeler, Simon Whelan, Jamey Wierzbowski, David L. Willey, S. C. P. Williams, Richard K. Wilson, Eitan Winter, Kim C. Worley, Dudley Wyman, Shan Yang, Shiaw-Pyng Yang, Evgeny M. Zdobnov, Michael C. Zody, Eric S. Lander
Bibliographic record
VenueNature · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsWestern UniversityBioinformatics Solutions (Canada)University of Waterloo
FundersNational Center for Research ResourcesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Cancer InstituteFogarty International CenterNational Institute of Mental HealthNatural Sciences and Engineering Research Council of CanadaNational Institute on Deafness and Other Communication DisordersEuropean Molecular Biology LaboratoryWellcome TrustNational Institute of General Medical SciencesBundesministerium für Bildung und ForschungGlaxoSmithKlineNational Institutes of HealthSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungU.S. Department of EnergyMinistry of Education, Culture, Sports, Science and TechnologyMedical Research CouncilHoward Hughes Medical InstituteFoundation for the National Institutes of HealthNational Science Foundation
KeywordsGenomeSyntenyBiologyComparative genomicsGeneComputational biologyGeneticsSequence analysisHuman genomeGenomicsWhole genome sequencingEvolutionary biology
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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 head0.026
GPT teacher head0.266
Teacher spread0.240 · 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 designBench or experimental
Domainnot available
GenreEmpirical
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
Citations7,249
Published2002
Admission routes2
Has abstractno