Hip replacement surgery: A scientometric assessment of global publications output during 2007–16
Bibliographic record
Abstract
The present study examined 4884 global hip replacement surgery publications, as indexed in Scopus database during 2007–16, with a view to understand their growth rate, global share, citation impact, international collaborative papers share, distribution of publications by broad subjects, productivity and citation profile of top organizations and authors, preferred media of communication and characteristics of high cited papers. The global publications registered an annual average growth rate of 4.98% and its citation impact averaged to 12.11 citations per paper. The global share of top 10 most productive countries ranged from 3.24% to 28.52%, with largest global publication share coming from USA (28.52%), followed by UK (13.53%), etc. Together, the top 10 most productive countries accounted for 80.51% global publication share during 2007–16, increasing from 80.04% to 80.82% from 2007–11 to 2012–16. The international collaborative publications share of top 10 countries varied from 10.45% to 39.05%, with the highest share coming from Canada (39.05%), followed by Australia (37.37%), Germany (29.61%), Netherlands (28.40%), France (27.87%), U.K. (27.84%), Italy (27.81%), etc. Among seven broad subjects, medicine contributed the largest publications share of 93.08%, followed by engineering (7.47%), biochemistry, genetics & molecular biology (5.55%) etc. during 2007–16. Among various organizations and authors contributing to hip replacement surgery, the 20 most productive global organizations and authors together contributed 20.86% and 10.24% respectively as their share of global publication output and 29.69% and 18.42% respectively as their share of global citation output. Among 4776 journal papers in hip replacement surgery research, the top 15 most productive journals contributed 40.10% share of total journal publication output. 37.61% to 41.76% from 2007–11 and 2012–16. 64 publications were found to be high cited, as they registered citations from 100 to 806 during 2007–16 and they together received 11683 citations, which averaged to 182.55 citations per paper.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".