Bibliographic record
Abstract
Editor-in-ChiefProf. (Mrs.) Smile DzisiKoforidua Technical University, GhanaManaging EditorDr. Frank Agyen DwomohKoforidua Technical University, Ghana Editorial Advisors Prof. Christopher SelvarajahSwinbume University of Technology, AustraliaProf. Mathew TsamenyiBirmingham University, UKProf. Ndao MomarMcGill University, CanadaProf. Raghavan VijayaMcGill University, CanadaProf. P.R. BanerjeeLondon Col. of Management Studies, LondonDr. Joel Osarcar BarimaLondon Col. of Management Studies, LondonDr. P. R. DattaLondon Col. of Management Studies, LondonDr. Rosemond BooheneUniversity of Cape Coast, GhanaProf. Benjamin SimpsonMcGill University, Canada Prof. Agnes KhooUniversity of Leeds, UK Prof. Mawutor AvokeUniversity of Education, Winneba, GhanaProf. D. Kofi MerekuUniversity of Education Winneba, Ghana Dr. William Gyedu-Asiedu Koforidua Technical University, Ghana Dr. Joseph Onumah- MensahUniversity of Ghana, GhanaDr. Angelina O. DanquahUniversity of Ghana, GhanaDr. George Owusu-DapaahKumasi Technical University, GhanaDr. Patricia Owusu-DarkoKumasi Technical University, GhanaDr. J. B. Hayfron-AcquahKwame Nkrumah University of Science andTechnology, Ghana Dr. John Bonney Koforidua Technical University, GhanaDr. Albert Kojo SunnuKwame Nkrumah University of Science and Technology, GhanaDr. Frank BamfoKoforidua Technical University, GhanaDr. K. Owusu AcheampongKoforidua Technical University, Ghana Dr. Mawuko Dza Koforidua Technical University, Ghana Dr. John Owusu Koforidua Technical University, Ghana Mr. Samuel Antwi Koforidua Technical University, Ghana Editorial AssistantsMrs. Patricia CrentsilMr. Solomon Ernest MensahMr. Emmanuel D.TettehMr. Emmanuel Opoku Debrah
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 | 0.007 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.265 | 0.197 |
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".