Spatial Abilities, Anatomy Knowledge and Technical Skills: A Systematic Review
Bibliographic record
Abstract
Objective Spatial abilities consist of visualization, orientation and manipulation of structures in space. Spatial abilities have been correlated to anatomy knowledge and the performance in technical skills in systematic reviews. The objective was to conduct a systematic review of the relationship between anatomy knowledge and performance in technical skills as related to spatial abilities. Methods Search criteria included ‘spatial abilities’, ‘anatomy knowledge’ and ‘technical skills’. Keywords related to these criteria were defined. A literature search was done up to December 31, 2014 in Scopus (including Medline) and in several databases on OvidSP and EBSCOhost platforms. A bank of citations was obtained and was reviewed by two independent investigators. Citations related to abstracts, literature review, thesis and books were excluded. Articles related to retained citations were obtained and a final list of articles was done. Articles were assessed for quality using Scottish Intercollegiate Guidelines Network‐50 (SIGN‐50). Data were extracted from articles and methods relating spatial abilities, anatomy knowledge and technical skills were identified. Results A series of 106 articles was obtained. One additional article was identified through other source. A series of 53 articles was identified after duplicates were removed. Forty‐nine articles were then excluded. Four articles were retained, fully reviewed, and excluded with reasons, yielding no eligible articles. Conclusion No eligible articles were found in a systematic review on spatial abilities, anatomy knowledge and technical skills. Future studies will be required to assess the importance of anatomy knowledge before performing a technical skill as related to spatial abilities. Support or Funding Information None.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".