VERTICAL SNARC WITH POSITIVE AND NEGATIVE NUMBERS
Bibliographic record
Abstract
Participants compared the magnitudes of pairs of vertically presented digits, viewed as temperatures, ranging from (-7,-6) through to (6,7). On half the trials the larger digit was selected and the smaller on the other half. Taken together, the findings show: 1) SNARC occurs in the vertical dimension for both positive and negative numbers; 2) the direction of the SNARC effect is not fixed but depends on the instruction; 3) the mental number line extends past zero to include negative numbers, and 4) SNARC was more robust when a thermometer was included. As well, semantic congruity effects were obtained: selection of the smaller of a pair of negative digits was faster than with the instruction “larger ” and selection of the larger of a pair of positive digits was faster than with the instruction “smaller”. These findings did not depend on whether the positive and negative pairs were intermixed or whether they were presented in separate blocks. The mental number line serves as the underlying mental representation of digits. On this view, a digit is represented as point on this line corresponding to its magnitude, i.e., an analogue representation. In addition to their representations as locations on an underlying analogue
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".