Structural and functional multi-platform MRI series of a single human volunteer over 15+ years
Bibliographic record
Abstract
We present MRI data from a single human volunteer consisting in over 599 multi-contrast MR images (T1- \nweighted, T2-weighted, proton density, fluid-attenuated inversion recovery, T2* gradient-echo, diffusion, \nsusceptibility-weighted, arterial-spin labelled, and resting state BOLD functional connectivity imaging) \nacquired in over 73 sessions on 36 different scanners (13 models, three manufacturers) over the course of \n15+ years (cf. Data records). Data included planned data collection acquired within the Consortium pour \nl’identification précoce de la maladie Alzheimer - Québec (CIMA-Q) and Canadian Consortium on \nNeurodegeneration in Aging (CCNA) studies, as well as opportunistic data collection from various protocols. \nThese multiple within- and between-centre scans over a substantial time course of a single, cognitively \nhealthy volunteer can be useful to answer a number of methodological questions of interest to the \ncommunity.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".