Part II: A CLIMBER Meta-analysis, recovery time measured by behavioral outcome tests after contusive injuries on various spinal levels in rats and mice of both sexes from 7 public datasets (Individual Animal Data (IAD)) corresponding to Part 1 Literature-Extracted Data
Bibliographic record
Abstract
STUDY PURPOSE: The purpose of the study was to analyze recovery after spinal cord injury through various different behavioral outcome tests. The study compared effect sizes from literature sourced (literature-extracted data (LED)) to the literatures’ corresponding publicly available raw data (individual animal data (IAD)). Random effect models and regression analyses were applied to evaluate predictors of neuro-conversion in LED versus IAD. Subgroup analyses were performed on animal sex, animal type, animal species, injury severity, injury segment and sample sizes. Publications with common injury models (contusive injuries) and standardized endpoints (open field assessments) were included in the meta-analyses. Studies that recorded open field assessments at 0-3 and 28-56 days past operation were included. This dataset includes the individual animal data (IAD) (part 2) that was collected for the study. The code to replicate our study can be found on github (https://github.com/ucsf-ferguson-lab/climber_meta_analysis2024.git). This dataset corresponds with another dataset in ODC-SCI (10.34945/F5DG6D) which contains data that was extracted directly from the 7 published articles, literature extracted data (LED). DATA COLLECTED: The individual animal data in this dataset was collected from raw data publicly available in ODC-SCI. This dataset includes merged data from 7 different publicly available datasets. Each study from the published articles includes contusion injuries with various severities and different locations, which are indicated in this dataset. Different mice and rat species are included in the dataset with both sexes. Outcome scores at different days-post operation from BBB, BMS, Grooming and Forelimb Open Field tests are also included. The behavioral outcome scores over days post operation were used to calculate effect sizes. DATA USAGE NOTES:
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.007 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; both teacher heads agree on what is shown here.
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".