Bibliographic record
Abstract
AHMET KUCUK, MDMersin City Education and Research Hospital, Radiation Oncology Clinics, Mersin, Turkey BERRIN PEHLIVAN, MDDepartment of Radiation Oncology, Bahcesehir University, Istanbul, Turkey BUSRA YILMAZ, DDS, MSCDepartment of Oral and Maxillofacial Radiology, Faculty of Dentistry, Baskent University, Ankara, Turkey CONSOLATO M. SERGI, MD, PHD, FRCPC, FCAPAnatomic Pathology Division, Children’s Hospital of Eastern Ontario (CHEO), University of Ottawa, Ottawa, ON, Canada; Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB, Canada DIANA NUNES, MSCDifferentiation and Cancer Group, Institute for Research and Innovation in Health (i3S) of the University of Porto, 4200-135 Porto, Portugal; Toxicology Research Unit (TOXRUN), University Institute of Health Sciences, Polytechnic and University Cooperative (CESPU), 4585-116 Gandra, Portugal DUYGU SEZEN, MDKoc University, School of Medicine, Department of Radiation Oncology, Istanbul, Turkey EFSUN SOMAY, DDS, PHDDepartment of Oral and Maxillofacial Surgery, Faculty of Dentistry, Baskent University, Ankara, Turkey ERKAN TOPKAN, MDDepartment of Oral and Maxillofacial Radiology, Faculty of Dentistry, Baskent University, Ankara, Turkey EYUB YASAR AKDEMIR, MDKoc University, School of Medicine, Department of Radiation Oncology, Istanbul, Turkey LAUREN M. WAINMAN, PHDDepartment of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, One Medical Center Drive, Lebanon, NH, USA MARIANA NUNES, MSCDifferentiation and Cancer Group, Institute for Research and Innovation in Health (i3S) of the University of Porto, 4200-135 Porto, Portugal; Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4050 313 Porto, Portugal NULIFER KILIC DURANKUS, MDKoc University, School of Medicine, Department of Radiation Oncology, Istanbul, Turkey PRABHJOT KAUR, MDDepartment of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, One Medical Center Drive, Lebanon, NH, USA SARA RICARDO, PHDDifferentiation and Cancer Group, Institute for Research and Innovation in Health (i3S) of the University of Porto, 4200-135 Porto, Portugal; Toxicology Research Unit (TOXRUN), University Institute of Health Sciences, Polytechnic and University Cooperative (CESPU), 485-116 Gandra, Portugal; Faculty of Medicine from University of Porto (FMUP), 4200-319 Porto, Portugal SUKRAN SENYUREK, MDKoc University, School of Medicine, Department of Radiation Oncology, Istanbul, Turkey UGUR SELEK, MDDepartment of Radiation Oncology, MD Anderson Cancer Center, The University of Texas, Houston, TX, USA;7Department of Radiation Oncology, Faculty of Medicine, Baskent University, Adana, Turkey WAHAB A. KHAN, PHDDepartment of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, One Medical Center Drive, Lebanon, NH, USA YASEMIN BOLUKBASI, MDKoc University, School of Medicine, Department of Radiation Oncology, Istanbul, Turkey
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 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 | 0.002 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.725 | 0.660 |
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; the direct Gemma label and the distilled Codex classifier 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".