Bibliographic record
Abstract
Dataset setting out to investigate behavioural and EEG responses to syllables coupled with tactile pulses at a 5Hz rhythm. The raw behavioural and EEG data is provided here. #Introduction This dataset contains the behavioural response to one syllable discrimination task in which subjects were subjected to regular tactile stimuli followed by a syllable in noise. It also contains the EEG response recorded during the task. There were 16 subjects, which IDs are : 'camembert', 'leader', 'bristol', 'policeman', 'frenchship', 'preacher', 'pretzel2new', 'canada', 'rotiqueen', 'kitten', 'batman', '2d', 'laundry2', 'bearcub', 'stopwatch' and 'tala'. #Content The dataset contains a folder named after each subject: these contain the eeg recordings for each of them as well as behavioural data. id_Entrainment.csv: This csv file contains all the behvioural data about the subject (id). The different fields are as follow: Trial: The ID of the current trial Type: Whether the tactile stimuli was audio-tactile rhythmic, audio-tactile random or audio-only Phase: In case it is audio-tactile, what is the phase between the onset of the vowel and the tactile rhythm. Note that we refer here to the phase relative to the rhythm of the tactile stimuli and not a measured rhythm. This choice was made as to sample the delays between audio and tactile as to be between 1 and 2 periods away from the rhythm we would expect to emerge from brain activity. The four phases can easily be translated to the following audio-tactile delays between the last tactile pulse and the onset of the syllable as: 150ms, 200ms, 250ms, 300ms. Score: 1 if the right syllable was selected by the subject, 0 otherwise. Syllable: the presented syllable out of the following set: ka, ga, ba, pa, da, ta Gender: The gender of the speaking voice, m for male, f for female Shift: A random shift between the onset of the trial and the first tactile pulse. Note that this value is representing the number of samples at a sampling frequency of 39062.5 (imposed by our hardware: TDT RX8) Random: The number of the random tactile stimulation. Since these were generated procedurally, we recorded them for reference, however, they do not play a part in the analysis. id.eeg, id.vhdr, id.vmrk: These correspond to the recorded data. More information on these file formats can be found on the Brian vision webpage. #EEG Data Format We recorded continuous EEG from the participants over an hour at 1kHz. In addition to the 63 channels, there is also Stimtrack channel labelled as 'Sound' which was tracking an addition of the auditory and tactile stimuli and allowed to track the sent stimuli as well as the alignment. The corresponding files can be found using the provided .csv file. The .vmrk file provided contains the timing of the triggers sent at the start of each trial and can help with tracking the progress in the experiment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.037 |
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".