Relationship between spatial abilities and cross‐sectional drawings
Bibliographic record
Abstract
Objective Spatial abilities have been related to cross‐sections of anatomical structures. The objective was to assess the relationship of spatial abilities to positioning and assessing area of structures in cross‐sectional 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). Participants had to draw by observation the four lateral sides of objects made of several structures. After the objects were removed from view, cross‐sections of the objects were drawn. Position and area of structures within drawn objects were compared to standard. Results were expressed as means ± standard deviation and Spearman's correlation coefficient was used to assess the relationship of positional and area errors of drawn structures to MRTA, MRTC and SDT scores. Results Positional error (9805 ± 6699 pixels) was inversely related to MRTA (13.5 ± 5.2), MRTC (9.7 ± 4.5) and SDT (43.4 ± 10.0) scores; with a correlation of − 0.3718 (p = 0.0085), − 0.4682 (p = 0.0007) and − 0.3461 (p = 0.0149), respectively. Similarly, area error (440416 ± 131870 pixels) was not related to MRTA, MRTC and SDT scores. Conclusion Spatial abilities were related to the position, but not to the area, of structures in cross‐sectional drawings of objects. 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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".