Bibliographic record
Abstract
Hilary Arksey & Lisa O'Malley (2005) Scoping studies: towards a methodological framework, International Journal of Social Research Methodology, 8:1, 19-32, DOI: 10.1080/1364557032000119616 Barreto, J. O. M., Silva, E. N. da, Gurgel-Gonçalves, R., Rosa, S. de S. R. F., Felipe, M. S. S., & Santos, L. M. P. (2019). Pesquisa translacional em saúde coletiva: desafios de um campo em evolução. Saúde Em Debate, 43(spe2), 4–9. https://doi.org/10.1590/0103-11042019s200 Canadian Institute of Health Researh. (2009). Knowledge translation strategy 2004-2009: Innovation in action. 1–16. https://cihr-irsc.gc.ca/e/documents/kt_strategy_2004-2009_e.pdf Clavier, C., Sénéchal, Y., Vibert, S., & Potvin, L. (2012). A theory-based model of translation practices in public health participatory research. Sociology of Health & Illness, 34(5), 791–805. https://doi.org/10.1111/j.1467-9566.2011.01408.x DA, E., da Motta e Albuquerque, E., & Cassiolato, J. (2002). As Especificidades do Sistema de Inovação do Setor Saúde1. Ver Econom Polít, 22. https://doi.org/10.1590/0101-31572002-1224 Etzkowitz, H., & Leydesdorff, L. (2000). The dynamics of innovation: From National Systems and “mode 2” to a Triple Helix of university-industry-government relations. Research Policy, 29(2), 109–123. https://doi.org/10.1016/S0048-7333(99)00055-4 Gadelha, C. A. G., Vargas, M. A., & Alves, N. G. (2019). Pesquisa translacional e sistemas de inovação na saúde: implicações para o segmento biofarmacêutico TT - Translational research and innovation systems in health: implications on the biopharmaceutical segment. Saúde debate, 43(spe2), 133–146. http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-11042019000600133 Gagliardi, A. R., Berta, W., Kothari, A., Boyko, J., & Urquhart, R. (2016). Integrated knowledge translation (IKT) in health care: a scoping review. Implement Sci, 11, 38. http://dx.doi.org/10.1186/s13012-016-0399-1 Gibbons, M., Limoges, C., Nowotny, Helga Schwartzman, S., Scott, P., & Trow, M. (1994). The New Production of Knowledge: The Dynamics of Science and Research in Contempoorary Societies. In SAGE Publications. MDJ, P., C, G., P, M., C, B. S., H, K., & D., P. (2017). Scoping Reviews: Joanna Briggs Institute Reviewer’s Manual. Joanna Briggs Institute. https://doi.org/10.46658 Pham et al., (2014). A scoping review of scoping reviews: advancing the approach and enhancing the consistency. Research Synthesis Methods published by John Wiley & Sons, Ltd. Res. Syn. Meth. 2014, 5 371–385 Woolf, S. H. (2008). The Meaning of Translational Research and Why It Matters. American Medical Association, 2011–2013. http://www.ahrq
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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.682 | 0.557 |
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".