Explicit mechanisms do not account for implicit localization and identification of change: An empirical reply to Mitroff et al. (2002).
Bibliographic record
Abstract
Several recent findings support the notion that changes in the environment can be implicitly represented by the visual system. S. R. Mitroff, D. J. Simons, and S. L. Franconeri (see record 2002-15293-003) challenged this view and proposed alternative interpretations based on explicit strategies. Across 4 experiments, the current study finds no empirical support for such alternative proposals. Experiment 1 shows that subjects do not rely on unchanged items when locating an unaware change. Experiments 2 and 3 show that unaware changes affect performance even when they occur at an unpredictable location. Experiment 4 shows that the unaware congruency effect does not depend simply on the pattern of the final display. The authors point to converging evidence from other methodologies and highlight several weaknesses in Mitroff et al's theoretical arguments. It is concluded here that implicit representation of change provides the most parsimonious explanation for both past and present findings. ((c) 2003 APA, all rights reserved)
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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 | 0.015 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.004 | 0.023 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.018 | 0.020 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".