Numerical Sequence Recognition: Is Familiarity or Ordinality the Primary Factor in Performance?
Bibliographic record
Abstract
Lyons and Beilock (2009) suggested that the degree of ordinal association in 3-digit numerical sequences is a primary factor in the speed and accuracy with which people recognize numerical sequences.Using two experiments I examined an alternative hypothesis, specifically that having automatic access to a larger set of memorized (i.e., familiar) sequences is the determining factor in performance.Participants were shown four types of ordered stimuli, with corresponding unordered sequences.In general, highly-skilled participants responded faster than their less-skilled counterparts.All participants were slower to reject unordered sequences that shared numbers with highly familiar sequences (e.g., 3 1 2) than with relatively unfamiliar unordered sequences (e.g., 7 1 2): this pattern is referred to as an interference effect.Participants were faster to identify familiar ascending than descending sequences, despite being equally ordered.These results support familiarity, and not ordinality, as the determining factor in sequence recognition.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".