Bibliographic record
Abstract
Declarations Funding The preparation of this review was not supported by any external funding. Authorship and Conflict of interest During the peer review process the manufacturer of the agent under review was offered an opportunity to comment on the article. Changes resulting from any comments received were made by the authors on the basis of scientific completeness and accuracy. Susan J. Keam is a contracted employee of Adis International Ltd/Springer Nature, and declares no relevant conflicts of interest. All authors contributed to the review and are responsible for the article content. Ethics approval, Consent to participate, Consent to publish, Availability of data and material, Code availability not applicable Additional information about this Adis Drug Review can be found here. Abstract Concizumab (Alhemo™), a subcutaneously administered humanised monoclonal IgG4 antibody against tissue factor pathway inhibitor (TFPI), binds to the Kunitz-2 domain of TFPI and prevents TFPI from binding to activated Factor X. Concizumab is being developed by Novo Nordisk for the treatment of hemophilia A and B with and without inhibitors. In March 2023, concizumab was approved in Canada for the treatment of adolescent and adult patients (12 years of age or older) with hemophilia B who have FIX inhibitors and require routine prophylaxis to prevent or reduce the frequency of bleeding episodes. This article summarizes the milestones in the development of concizumab leading to this first approval for the treatment of hemophilia B. © Springer Nature Switzerland AG 2023
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.327 | 0.231 |
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".