Update fixation whitepaper link to Algorithm description - 3.6.24

neon/data-collection/data-streams/index.md

@@ -24,16 +24,16 @@
 
 The gaze estimation algorithm is based on end-2-end deep learning and provides gaze data robustly without requiring a calibration. You can find a high-level description as well as a thorough evaluation of the accuracy and robustness of the algorithm in our [white paper](https://zenodo.org/doi/10.5281/zenodo.10420388). 
 
 ## Fixations & Saccades
 
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 The two primary types of eye movements exhibited by the visual system are fixations and saccades. During fixations, the eyes are directed at a specific point in the environment. A saccade is a very quick movement where the eyes jump from one fixation to the next. Properties like the fixation duration are of significant importance for studying gaze behavior.
 
 ![Fixations](./fixations.jpg)
 
-Fixations and saccades are calculated automatically in Pupil Cloud after uploading a recording and are included in the recording downloads. The deployed fixation detection algorithm was specifically designed for head-mounted eye trackers and offers increased robustness in the presence of head movements. Especially movements due to vestibulo-ocular reflex are compensated for, which is not the case for most other fixation detection algorithms. You can learn more about it in the [Pupil Labs fixation detector whitepaper](https://docs.google.com/document/d/1dTL1VS83F-W1AZfbG-EogYwq2PFk463HqwGgshK3yJE/export?format=pdf) and in our [publication](https://link.springer.com/article/10.3758/s13428-024-02360-0) in *Behavior Research Methods* discussing fixation detection strategies.
+Fixations and saccades are calculated automatically in Pupil Cloud after uploading a recording and are included in the recording downloads. The deployed fixation detection algorithm was specifically designed for head-mounted eye trackers and offers increased robustness in the presence of head movements. Especially movements due to vestibulo-ocular reflex are compensated for, which is not the case for most other fixation detection algorithms. You can learn more about it in the [Pupil Labs fixation detector whitepaper](https://docs.google.com/document/d/1CZnjyg4P83QSkfHi_bjwSceWCTWvlVtbGWtuyajv5Jc/export?format=pdf) and in our [publication](https://link.springer.com/article/10.3758/s13428-024-02360-0) in *Behavior Research Methods* discussing fixation detection strategies.
 
 We detect saccades based on the fixation results, considering the gaps between fixations to be saccades. Note, that this assumption is only true in the absence of smooth pursuit eye movements. Additionally, the fixation detector does not compensate for blinks, which can cause a break in a fixation and thus introduce a false saccade.
 
 The downloads for gaze mapping enrichments ([Reference Image Mapper](/pupil-cloud/enrichments/reference-image-mapper/#export-format), [Marker Mapper](/pupil-cloud/enrichments/marker-mapper/#export-format)) also include mapped fixations, i.e. fixations in reference image or surface coordinates respectively.