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Radiologists staunchly support patient safety and autonomy, in opposition to the SCOTUS decision to overturn Roe v Wade
Aditya Karandikar, Agnieszka O. Solberg, Alice Fung, Amie Y. Lee, Amina Farooq, Amy Taylor, Amy Oliveira, Anand K. Narayan, Andi Senter, Aneesa Majid, Angela Tong, Anika L. McGrath, Anjali Malik, Ann L. Brown, Anne C. Roberts, Arthur C. Fleischer, Beth Vettiyil, Beth Zigmund, Brian Park, Bruce Curran, Cameron Henry, Camilo Jaimes, Cara Connolly, Caroline D. Robson, Carolyn C. Meltzer, Catherine H. Phillips, Christine Dove, Christine M. Glastonbury, Christy B. Pomeranz, Claudia Kirsch, Constantine M. Burgan, Courtney Scher, Courtney M. Tomblinson, Cristina Fuss, Cynthia Santillan, Dania Daye, Daniel B. Brown, Daniel J. Young, Daniel B. Kopans, Daniel Vargas, Dann Martin, D. J. Thompson, David W. Jordan, Deborah R. Shatzkes, Derek Sun, Domenico Mastrodicasa, Elainea N. Smith, Elena Korngold, Elizabeth H. Dibble, Elizabeth Kagan Arleo, Elizabeth M. Hecht, Elizabeth A. Morris, Elizabeth P. Maltin, Erin A. Cooke, Erin Simon Schwartz, Evan Lehrman, Faezeh Sodagari, Shah Faisal, Florence X. Doo, Francesca Rigiroli, George K. Vilanilam, Gina Landinez, Grace Gwe-Ya Kim, Habib Rahbar, Hailey H. Choi, Harmanpreet Bandesha, Haydee Ojeda‐Fournier, Ichiro Ikuta, I. Dragojević, Jamie Lee Twist Schroeder, Jana Ivanidze, Janine Katzen, Jason Chiang, Jeffers Nguyen, Jeffrey D. Robinson, Jennifer C. Broder, Jennifer Kemp, Jennifer S. Weaver, Jesse M. Conyers, Jessica B. Robbins, Jessica R. Leschied, Jessica Wen, Jocelyn Park, John Mongan, Jordan D. Perchik, José Pablo Martínez Barbero, Jubin Jacob, Karyn A. Ledbetter, Katarzyna J. Macura, Katherine E. Maturen, Katherine Frederick-Dyer, Katia Dodelzon, Kayla Cort, Kelly Kisling, Kemi Babagbemi, Kevin C. McGill, Kevin J. Chang, Kimberly Feigin, Kimberly S. Winsor, Kimberly Seifert, Kirang Patel, Kristin K. Porter, Kristin Foley, Krupa Patel-Lippmann, Lacey McIntosh, Laura Padilla, Lauren K. Groner, Lauren M. Harry, Lauren M. Ladd, Lisa Wang, Lucy B. Spalluto, M. Mahesh, M. Victoria Marx, Mark Sugi, Marla B. K. Sammer, Maryellen Sun, Matthew J. Barkovich, Matthew J. Miller, Maya Vella, Melissa A. Davis, Meridith J. Englander, Michael Durst, Michael Oumano, Monica J. Wood, Morgan P. McBee, Nancy J. Fischbein, Nataliya Kovalchuk, Neil Lall, Neville Eclov, Nikhil Madhuripan, Nikki S. Ariaratnam, Nina S. Vincoff, Nishita Kothary, Noushin Yahyavi‐Firouz‐Abadi, Olga R. Brook, Orit A. Glenn, Pamela K. Woodard, Parisa Mazaheri, Patricia Rhyner, Peter R. Eby, Preethi Raghu, Rachel F. Gerson, Rina Patel, Robert L. Gutierrez, Robyn Gebhard, Rochelle F. Andreotti, Rukya Masum, Ryan Woods, Sabala Mandava, Samantha G. Harrington, Samir Parikh, Sammy Chu, Sandeep Arora, Sandra M. Meyers, Sanjay P. Prabhu, Sara Shams, Sarah K. Pittman, S. Patel, Shelby Payne, Steven W. Hetts, Tarek A. Hijaz, Teresa Chapman, Thomas W. Loehfelm, Titania Juang, Toshimasa Clark, Valeria Potigailo, Vinil Shah, Virginia B. Planz, Vivek Kalia, Wendy B. DeMartini, William P. Dillon, Yasha Gupta, Yilun Koethe, Zachary Hartley-Blossom, Zhen J. Wang, Geraldine McGinty, Adina Haramati, Laveil M. Allen, Pauline Germaine
Bibliographic record
VenueClinical Imaging · 2022
Typeletter
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
FundersMcGill University
KeywordsMedicineAutonomySupreme courtAbortionHealth carePregnancyFamily medicineGeneral surgeryMedical emergencyLaw
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)0.011
metaresearch head score (Gemma)0.058
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.221
Threshold uncertainty score0.204
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.009 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.221 | 0.113 |
| Insufficient payload (model declined to judge) | 0.011 | 0.007 |
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 head0.086
GPT teacher head0.478
Teacher spread0.392 · 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
GenreCommentary
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
Citations3
Published2022
Admission routes1
Has abstractno