Verb fluency – noun fluency and the pathology of anterior versus posterior brain region. Do only grammatical features of tasks affect performance?
Bibliographic record
Abstract
ENWEndNote BIBJabRef, Mendeley RISPapers, Reference Manager, RefWorks, Zotero AMA Szepietowska EM, Kuzaka A. Verb fluency – noun fluency and the pathology of anterior versus posterior brain region. Do only grammatical features of tasks affect performance?. Neuropsychiatria i Neuropsychologia/Neuropsychiatry and Neuropsychology. 2018;13(1):17-25. doi:10.5114/nan.2018.77450. APA Szepietowska, E. M., & Kuzaka, A. (2018). Verb fluency – noun fluency and the pathology of anterior versus posterior brain region. Do only grammatical features of tasks affect performance?. Neuropsychiatria i Neuropsychologia/Neuropsychiatry and Neuropsychology, 13(1), 17-25. https://doi.org/10.5114/nan.2018.77450 Chicago Szepietowska, Ewa M, and Anna Kuzaka. 2018. "Verb fluency – noun fluency and the pathology of anterior versus posterior brain region. Do only grammatical features of tasks affect performance?". Neuropsychiatria i Neuropsychologia/Neuropsychiatry and Neuropsychology 13 (1): 17-25. doi:10.5114/nan.2018.77450. Harvard Szepietowska, E., and Kuzaka, A. (2018). Verb fluency – noun fluency and the pathology of anterior versus posterior brain region. Do only grammatical features of tasks affect performance?. Neuropsychiatria i Neuropsychologia/Neuropsychiatry and Neuropsychology, 13(1), pp.17-25. https://doi.org/10.5114/nan.2018.77450 MLA Szepietowska, Ewa et al. "Verb fluency – noun fluency and the pathology of anterior versus posterior brain region. Do only grammatical features of tasks affect performance?." Neuropsychiatria i Neuropsychologia/Neuropsychiatry and Neuropsychology, vol. 13, no. 1, 2018, pp. 17-25. doi:10.5114/nan.2018.77450. Vancouver Szepietowska E, Kuzaka A. Verb fluency – noun fluency and the pathology of anterior versus posterior brain region. Do only grammatical features of tasks affect performance?. Neuropsychiatria i Neuropsychologia/Neuropsychiatry and Neuropsychology. 2018;13(1):17-25. doi:10.5114/nan.2018.77450.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".