Replication Data for: Palaeoecological signals remain robust at broad spatiotemporal scales despite artificial reductions in sampling power and geographical scope
Bibliographic record
Abstract
This repository contains the data and code to replicate the results for 3.1, 3.2, or 3.3 in the paper titled "Palaeoecological signals remain robust at broad spatiotemporal scales despite artificial reductions in sampling power and geographical scope." It also contains the citations for the data used in the analysis. Project summary: Palaeoecological analyses rely on datasets that are comprised of collections or observations of fossil specimens. When palaeoecologists consider the scope of a novel project or research question, logistical constraints surrounding specimen acquisition are often a primary limiting factor. Despite this, some exceptional datasets exist that are both broad in spatiotemporal scope and densely sampled. One such dataset, consisting of 116,896 fossil brachiopods from central Nevada spanning from the beginning of the Early Devonian to the end of the Middle Devonian, is utilized by the present study as a model dataset to test the effects of logistically imposed restrictions on sample collection. Specifically, the present study tests whether palaeoecological signals (as represented in an NMDS ordination plot), and the processes that drive them, may be identified despite artificial reductions in spatiotemporal resolution and scope. These artificial reductions simulated two types of logistical sampling constraints: (1) limitations on the absolute number of samples collected, and (2) inability to travel to, and collect from, geographically separated regions. The primary palaeoecological signal identified in NMDS ordination plots of the entire dataset (255 samples) was identifiable more than >98% of the time with as few as 26 randomly selected samples, and NMDS ordinations of geographically restricted subsamples representing temporal intervals of >5 Ma were found to contain signals representative of the entire study area. Thus, it was possible to capture the primary signals corresponding to biodiversity shifts on broad scales with limited sampling power, and without extensively sampling outside of a single geographical region.
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 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 | 0.020 | 0.162 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.343 | 0.209 |
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".