The Use of Paired Comparisons for Evaluating Complex Route Matching Performance in a Spatial Awareness Task
Bibliographic record
Abstract
A method is proposed for evaluating participants’ performance in a global spatial awareness task involving identification of complex winding routes. Rather than using coarse measures of spatial error, the method of paired comparisons employs impartial judges to compare sets of aggregated experimental data generated by the participants with respect closeness in shape to the target route. The method was applied to a set of data in an experimental investigation of the effect of height on a participant’s ability to identify the route he had just flown over (in a 20 second video). Seven participants performed a total of 48 trials in a 4 (heights) X 2 (trial blocks) within-subjects experiment. Results from the paired comparison analysis suggested that height had a statistically significant effect on correct route identification. Of equal importance in the context of the present paper, the method of paired comparison analysis proved to be effective in quantifying performance data that did not otherwise lend themselves to conventional methods of quantification.
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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".