Relationship between spatial abilities and three‐dimensional synthesis of structures
Bibliographic record
Abstract
Objective The mental image of a three‐dimensional anatomical structure is a prerequisite to the performance in technical skills. The objective was to assess the relationship of spatial abilities to three‐dimensional synthesis of two‐dimensional views of structures using drawings. Methods Fourth‐year medical students (n = 49) were recruited in a prospective study. Spatial abilities were measured with a redrawn Vandenberg and Kuse Mental Rotations Test in two (MRTA) and three (MRTC) dimensions and the Surface Development Test (SDT). As part of a drawing course, participants had to build structures of increasing complexity from simple parts using two‐dimensional views of structures and then to draw isometric views of structures. The accuracy of the drawings was assessed as right or wrong. The maximum score was 24 for MRTA and MRTC, 60 for SDT and 25 for the drawings. The results were expressed as means ± standard deviation and the Spearman's correlation coefficient was used to compare the drawing score to MRTA, MRTC and SDT scores. Results The drawing score (14.6 ± 3.7) was related to MRTA (13.5 ± 5.2), MRTC (9.7 ± 4.5) and SDT (43.4 ± 10.0) scores; with a correlation of 0.3728 (p = 0.0083), 0.4248 (p = 0.0023) and 0.5420 (p < 0.0001), respectively. Conclusion Spatial abilities were related to three‐dimensional synthesis of two‐dimensional views of structures using drawings. This study was supported by an internal grant from the Department of Surgery, University of Sherbrooke, Sherbrooke, QC, Canada.
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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 | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".