The cognitive architecture of processes responsible to assess similarity and clarity in a comparison task
Bibliographic record
Abstract
When asked to compare two stimuli, participants are on average faster to respond Same than Different, an effect coined the fast-same. The dual-process theory argues that information about similarity is processed in priority over any other type of information, causing the fast-same effect. We tested this serial architecture of cognitive processes using a double factorial paradigm, suitable for a Systems Factorial Technology (SFT) analysis. Twenty participants completed a task in which they compared two letters, which were varied on two dimensions: the similarity and the clarity of the letters. Their task was to indicate if the second letter was the Same as the second letter (ranging from identical and clear to similar and slightly blurry) or if it was Different (if the stimuli were either dissimilar or very blurry). The SFT results show that most participants processed the information in serial, but in a mixed order. In other words, for some trials, participants processed similarity first, and for some other trials, they processed clarity first. This implies that participant indeed processed information in serial in the comparison task, but that it does not cause the fast-same effect.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".