Erratum: “The NANOGrav 15 yr Data Set: Search for Signals from New Physics” (2023, ApJL 951 L11)
Bibliographic record
Abstract
Erratum: “The NANOGrav 15 yr Data Set: Search for Signals from New Physics” (2023, ApJL 951 L11), Adeela Afzal, Gabriella Agazie, Akash Anumarlapudi, Anne M. Archibald, Zaven Arzoumanian, Paul T. Baker, Bence Bécsy, Jose Juan Blanco-Pillado, Laura Blecha, Kimberly K. Boddy, Adam Brazier, Paul R. Brook, Sarah Burke-Spolaor, Rand Burnette, Robin Case, Maria Charisi, Shami Chatterjee, Katerina Chatziioannou, Belinda D. Cheeseboro, Siyuan Chen, Tyler Cohen, James M. Cordes, Neil J. Cornish, Fronefield Crawford, H. Thankful Cromartie, Kathryn Crowter, Curt J. Cutler, Megan E. DeCesar, Dallas DeGan, Paul B. Demorest, Heling Deng, Timothy Dolch, Brendan Drachler, Richard von Eckardstein, Elizabeth C. Ferrara, William Fiore, Emmanuel Fonseca, Gabriel E. Freedman, Nate Garver-Daniels, Peter A. Gentile, Kyle A. Gersbach, Joseph Glaser, Deborah C. Good, Lydia Guertin, Kayhan Gültekin, Jeffrey S. Hazboun, Sophie Hourihane, Kristina Islo, Ross J. Jennings, Aaron D. Johnson, Megan L. Jones, Andrew R. Kaiser, David L. Kaplan, Luke Zoltan Kelley, Matthew Kerr, Joey S. Key, Nima Laal, Michael T. Lam, William G. Lamb, T. Joseph W. Lazio, Vincent S. H. Lee, Natalia Lewandowska, Rafael R. Lino dos Santos, Tyson B. Littenberg, Tingting Liu, Duncan R. Lorimer, Jing Luo, Ryan S. Lynch, Chung-Pei Ma, Dustin R. Madison, Alexander McEwen, James W. McKee, Maura A. McLaughlin, Natasha McMann, Bradley W. Meyers, Patrick M. Meyers, Chiara M. F. Mingarelli, Andrea Mitridate, Jonathan Nay, Priyamvada Natarajan, Cherry Ng, David J. Nice, Stella Koch Ocker, Ken D. Olum, Timothy T. Pennucci, Benetge B. P. Perera, Polina Petrov, Nihan S. Pol, Henri A. Radovan, Scott M. Ransom, Paul S. Ray, Joseph D. Romano, Shashwat C. Sardesai, Ann Schmiedekamp, Carl Schmiedekamp, Kai Schmitz, Tobias Schröder, Levi Schult, Brent J. Shapiro-Albert, Xavier Siemens, Joseph Simon, Magdalena S. Siwek, Ingrid H. Stairs, Daniel R. Stinebring, Kevin Stovall, Peter Stratmann, Jerry P. Sun, Abhimanyu Susobhanan, Joseph K. Swiggum, Jacob Taylor, Stephen R. Taylor, Tanner Trickle, Jacob E. Turner, Caner Unal, Michele Vallisneri, Sonali Verma, Sarah J. Vigeland, Haley M. Wahl, Qiaohong Wang, Caitlin A. Witt, David Wright, Olivia Young, Kathryn M. Zurek, The NANOGrav Collaboration
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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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.096 | 0.106 |
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.
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.
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".