Rethinking social aging through multilayer network analysis
Bibliographic record
Abstract
Rethinking social aging through multilayer network analysis Description of the data and file structure Data were collected between November 2008 and November 2018 from three troops of wild vervet monkeys occupying adjacent and overlapping home ranges in the Samara Private Game Reserve in the semiarid Karoo biome, Eastern Cape, South Africa (Pasternak et al. 2013). The three study groups, RST (mean ± SD group size: 50±9), RBM (43±10) and PT (37±11), have been fully habituated since 2008 (RST and RBM) and 2012 (PT). For all offspring born from the 2009 birth season onwards, ages were known to within 1 day for RBM and RST troops, while birth dates were known from the 2012 birth season onwards for PT troop. For individuals already present at the start of the study period (November 2008 for RST and RBM, and July 2012 for PT), as their exact ages could not be determined, they were categorized as adult, subadult, juvenile or yearling. All animals were individually identifiable from natural markings.Each troop was followed on foot by one or more researchers on each 10 h study day, for 3-5 days per week per troop (RBM: 1440 days; RST: 1509 days; PT: 1021 days). We used electronic hand-held data loggers and commercial software to record data from all visible animals, using scan samples conducted every 30 min (Young et al. 2017). Each scan sample lasted 10 min, during which we collected data on each animal’s activity (feeding, moving, resting and grooming) and the identity of its nearest female, male and juvenile neighbours. When animals were recorded as grooming, we noted the identity of their partners. Files and variables File: NDVIRZone.csv Description: Environmental data (NDVI) Variables Date: NDVI: File: environment_to_load.RData Description: This contains the needed datasets (grooming interactions, age information, as well as dataset to infer troop size) for you to be able to run the code File: MLNA_Social_aging_full.Rmd Description: The r code used for the analysis Code/software RStudio was used on an online server to enable faster computation during the modeling steps. However, the code can also be run locally in R, though some of the larger models may take longer to execute.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".