Supplement 1. Richness response, ANPP, and climate data for all studies included in the meta-analysis.
Bibliographic record
Abstract
File List encroach_div_data.txt (md5: f755284466bd9e2836b9171063d5b016) Description The encroach_div_data.txt file is a tab separate file. It contains the raw data used to calculate "community type" averages of richness response and ANPP. It also includes meta-data about each study included, such as the corresponding citations, study site location, study design, and yearly climate averages (precipitation and temperature). Column descriptions: 1. Community_Type = the name of the community type that the study was categorized as 2. Richness_Cit = the first author name and year for of each site richness data 3. ANPP_Cit = the first author name and year for of each site richness data 4. Location= the location where the study took place, usually a nearby city, wildlife refuge or research station 5. State/Province = U.S. state or Canadian province where the study took place 6. Encroaching_Species: species name of the predominate encroaching species in the study 7. Study_Design = the type of study design used to compare encroached and unencroaced richness ('WvG' denotes a binary comparison between encroached and unencroached treatments in the same year[s] with species richness expressed as the number of species per plot, 'Inven' denotes a binary comparison between encroached and unencroached treatments in the same year[s] with species richness expressed as the total number of species found in unencroached and encroached treatments, 'HC' denotes a binary comparison before and after encroachment occurred in the same plots with species richness expressed as the number of species per plot, 'REG' denotes a comparison of woody cover [%] to species richness in the same year[s] with species richness expressed as the number of species per plot) 8. Latitude = latitude of the study site (decimal degrees) 9. Longitude: longitude of the study site (decimal degrees) 10. MAP = mean annual precipitation at the study site (mm/yr)_ 11. MAT = mean annual temperature of the study site (°C) 12. Richness_Response: richness response (unitless) 13. ANPP_Unencroached = annual aboveground net primary productivity measured in unencroached plots (g/ 14. ANPP_Encroached = annual aboveground net primary productivity measured in encroached plots (g/m<sup>2</sup>) Missing values are represented as "---" Check-sum values are: Column 8 (Latitude): SUM = 1186.73; 0 values missing (rows with data: 30) Column 9 (Longitude): SUM = -31870.377; 0 values missing (rows with data: 30) Column 10 (MAP): SUM = 16652.360; 0 values missing (rows with data: 30) Column 11 (MAT): SUM = 324.211; 0 values missing (rows with data: 30) Column 12 (Richness_response): SUM = -19.494; 0 values missing (rows with data: 30) Column 13 (ANPP_Unencroaced): SUM = 4500.100; 13 values missing (rows with data: 17) Column 14 (ANPP_Encroached): SUM = 13248.200; 12 values missing (rows with data: 18)
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 | 0.006 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.713 | 0.058 |
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".