Validation of an open source, web-based, eye-tracking method (WebGazer) for research on cognitive development: Comparison of anticipatory looking behavior in toddlers tested via web-based vs. in-lab eye-tracking
Bibliographic record
Abstract
In this multi-lab project, which is a part of the ManyBabies Project, we try to validate an open source, web-based, eye-tracking method for research on cognitive development in young children. More specifically, we evaluate whether this method, which is based on WebGazer.js (Papoutsaki et al., 2016) and jsPsych (de Leeuw, 2015), is comparable to lab-based eye-tracking. Therefore, we aim to replicate findings of an in-lab paradigm of the ManyBabies2 project, which revealed spontaneous goal-directed action anticipation in toddlers using commercial eye-tracking systems (Schuwerk, Kampis et al., 2021).
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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 | 0.031 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".