Biases in Measuring the Brain: The Trouble with the Telencephalon
Bibliographic record
Abstract
When correlating behavior with particular brain regions thought responsible for the behavior, a different region of the brain is usually measured as a control region. This technique is often used to relate spatial processes with the hippocampus, while concomitantly controlling for overall brain changes by measuring the remainder of the telencephalon. We have identified two methods in the literature (the HOM and TTM) that estimate the volume of the telencephalon, although the majority of studies are ambiguous regarding the method employed in measuring the telencephalon. Of these two methods, the HOM might produce an artificial correlation between the telencephalon and the hippocampus, and this bias could result in a significant overestimation of the relative hippocampal volume and a significant underestimation of the telencephalon volume, both of which are regularly used in large comparative analyses. We suggest that future studies should avoid this method and all studies should explicitly delineate the procedures used when estimating brain volumes.
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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 | 0.044 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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 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".