the washington manual of medical therapeutics
Bibliographic record
Abstract
1: Patient Care in Internal Medicine Mark Thoelke and Christopher J. Gutjahr 2: Nutrition Support Dominic Reeds 3: Preventative Cardiology and Ischemic Heart Disease Angela L. Brown, Anne Goldberg, Kory Lavine, Andrew Kates, and Neville Mistry 4: Heart Failure, Cardiomyopathy and Valvular Heart Disease Brian R. Lindman, Stacy A. Mandras, Benico Barzilai, Susan M. Joseph, and Gregory A. Ewald 5: Cardiac Arrhythmias Shivak Sharma, Daniel H. Cooper, and Mitchell N. Faddis 6: Critical Care Marin H. Kollef, Scott T. Micek, and Jen Alexander-Brett 7: Pulmonary Diseases Lee Demertzis, Tonya Russell, Robert M. Senior, Mario Castro, Luke Carlstrom, Murali Chakinala, Meena Murugappan, Alexander Chen, Ara Chrissian, Devin Sherman, Raksha Jain, and Daniel B. Rosenbluth 8: Allergy and Immunology Shirley Joo, Ritu Gupta, and Andrew Kau 9: Fluid and Electrolyte Management Bala Sankarpandian and Steven Cheng 10: Renal Diseases Seth Goldberg and Daniel Coyne 11: Treatment of Infectious Diseases Jose E. Hagan, Hillary M. Babcock, and Nigar Kirmani 12: Antimicrobials David J. Ritchie and Bernard C. Camins 13: Human Immunodeficiency Virus and Acquired Immunodeficiency Syndrome Diana Nurutdinova and Turner Overton 14: Solid Organ Transplant Medicine Brent W. Miller 15: Gastrointestinal Diseases C. Prakash Gyawali and Ahmad Manasra 16: Liver Diseases Mauricio Lisker-Melman and Anil B. Seetharam 17: Disorders of Hemostasis and Thrombosis Roger Yusen, Charles Eby, and Brian F. Gage 18: Anemia and Transfusion Therapy Reshma Rangwala and Morey Blinder 19: Medical Management of Malignant Disease Boone Goodgame, Daniel Morgensztern, and Ramaswamy Govindan 20: Diabetes Mellitus and Related Disorders Janet McGill 21: Endocrine Diseases William E. Clutter 22: Arthritis and Rheumatologic Diseases Hector Molina, Christopher Phillips, and Vladimir Despotovic 23: Neurologic Disorders Victoria Sharma and Beau Ances 24: Medical Emergencies S. Eliza Halcomb, Stephan Brenner, and Michael Mullins Appendix A: Immunizations and Post-Exposure Therapies Appendix B: Infection Control and Isolation Recommendations Appendix C: Advanced Cardiac Life Support Algorithms
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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.
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; both teacher heads agree on what is shown here.
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".