Editorial Commitment to Trust and Integrity in Science: Implications for Pain and Anesthesiology Research
Bibliographic record
Abstract
Tonya M Palermo,1,2 Didier Bouhassira,3 Karen Deborah Davis,4,5 Hugh C Hemmings Jnr,6 Robert W Hurley,7 Joel Katz,8 Jaideep Pandit,9,10 Theodore Price,11 Michael E Schatman,12,13 Stephan K W Schwarz,14,15 Dennis Turk,1 Marc Van de Velde,16,17 Matthew Wiles,18,19 Tony Yaksh,20 David Yarnitsky21 1Department of Anesthesiology & Pain Medicine, University of Washington, Seattle, WA, USA; 2Center for Child Health, Behavior & Development, Seattle Children’s Research Institute, Seattle, WA, USA; 3Inserm U987, APHP, UVSQ, Paris-Saclay University, Ambroise Pare Hospital, Boulogne-Billancourt, France; 4Department of Surgery and Institute of Medical Science, University of Toronto, Toronto, ON, Canada; 5Krembil Brain Institute, University Health Network, Toronto, ON, Canada; 6Department of Anesthesiology, Weill Cornell Medicine, New York, NY, USA; 7Department of Anesthesiology, Translational Neuroscience (formerly Pharmacology), and Public Health Sciences, Pain Outcomes Lab, Wake Forest University School of Medicine, Winston-Salem, NC, USA; 8Department of Psychology, York University, Toronto, ON, Canada; 9Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK; 10Nuffield Department of Anaesthesia, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; 11Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, Dallas, TX, USA; 12Department of Anesthesiology, Perioperative Care, and Pain Medicine, NYU Grossman School of Medicine, New York, New York, USA; 13Department of Population Health – Division of Medical Ethics, NYU Grossman School of Medicine, New York, New York, USA; 14Department of Anesthesiology, Pharmacology & Therapeutics, The University of British Columbia, Vancouver, BC, Canada; 15Department of Anesthesia, St. Paul’s Hospital/Providence Health Care, Vancouver, BC, Canada; 16Department of Cardiovascular Sciences, Catholic University Leuven, Leuven, Belgium; 17Department of Anesthesiology, University Hospitals Leuven, Leuven, Belgium; 18Department of Academic Anaesthesia, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK; 19Centre for Applied Health and Social Care Research (Care), Sheffield Hallam University, Sheffield, UK; 20Department of Anesthesiology & Pharmacology, University of California, San Diego, CA, USA; 21Department of Neurology, Rambam Medical Center, and Laboratory of Clinical Neurophysiology, Technion Faculty of Medicine, Haifa, IsraelCorrespondence: Tonya M Palermo, Seattle Children’s Research Institute, P.O. Box 5371, M/S BC-3, Seattle, WA, 98145, USA, Email tonya.palermo@seattlechildrens.org
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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 | 0.033 | 0.147 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.022 | 0.027 |
| Insufficient payload (model declined to judge) | 0.014 | 0.009 |
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".