Retraction Note: Eye tracking: empirical foundations for a minimal reporting guideline
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
The authors have retracted this article because a number of statements are supported by two references, Holmqvist (2015) and Holmqvist (2016), which should not have been used. Saga Lee Örbom, Ignace T. C. Hooge, Diederick C. Niehorster, Robert G. Alexander, Richard Andersson, Jeroen S. Benjamins, Pieter Blignaut, Anne-Marie Brouwer, Lewis L. Chuang, Kirsten A. Dalrymple, Denis Drieghe, Matt J. Dunn, Ulrich Ettinger, Susann Fiedler, Tom Foulsham, Jos N. van der Geest, Dan Witzner Hansen, Samuel B. Hutton, Enkelejda Kasneci, Alan Kingstone, Paul C. Knox, Ellen M. Kok, Helena Lee, Joy Yeonjoo Lee, Jukka M. Leppänen, Stephen Macknik, Päivi Majaranta, Susana Martinez-Conde, Antje Nuthmann, Marcus Nyström, Jacob L. Orquin, Jorge Otero-Millan, Soon Young Park, Stanislav Popelka, Frank Proudlock, Frank Renkewitz, Austin Roorda, Michael Schulte-Mecklenbeck, Bonita Sharif, Frederick Shic, Mark Shovman, Mervyn G. Thomas, Ward Venrooij, Raimondas Zemblys and Roy S. Hessels agree with this retraction. Kenneth Holmqvist is deceased.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.062 | 0.561 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.026 | 0.041 |
| Insufficient payload (model declined to judge) | 0.017 | 0.017 |
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".