Hepatitis B, Rituximab, Screening, and Prophylaxis: Effectiveness and Cost Effectiveness
Bibliographic record
Abstract
An important role of medical journals is to communicate infor-mation between stakeholder groups.1,2 These communications may be between researchers about findings that inform future research; results of phase I-II trials in Journal of Clinical Oncology (JCO) exem-plify thispurpose.Alternately, communicationsbetweenpractitioners can advise about implementing clinical practices, such as with narra-tive reviews and case-based manuscripts including JCO’s Oncology GrandRounds,which provide guidance to practitioners.3 Communi-cations from investigators to practitioners and policy makers include results of randomizedcontrolled trials (RCTs) and systematic reviews. These communications informdecisions aboutmanaging individual pa-tients and health care delivery policies. For policy determination, eco-nomic evaluations alsohave an important role. Implicit in conductingan economicanalysis ispriordemonstrationthattheinterventioniseffective. With this knowledge in hand, understanding economic ramifications of
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 | 0.005 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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; 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".