Additional file 1 of Unveiling the hidden economic toll of biological invasions in the European Union
Bibliographic record
Abstract
Additional file 1: Description of the sectors considered in the InvaCost database. Additional file 2: Site-level costs recorded in InvaCost for the European Union member states (a), by type of cost (b) and impacted sector (c) with and without high-leverage points and the respective projected additional cost and percent increase. Additional file 3: Detailed breakdown of the considered models included in the model averaging. Table 1: Country-level analyses. Values of the fitted parameters for each predictor combination and model performance estimated using Akaike’s information criterion (AIC). We calculated Akaike’s weights for model averaging following Burnham & Anderson [57]. Table 2: Country-level analyses without high-leverage points. Values of the fitted parameters for each predictor combination and model performance estimated using Akaike’s information criterion (AIC). Model outputs for each combination of predictors. We calculated Akaike’s weights for model averaging following Burnham & Anderson [57]. Table 3: Site-level analyses (A) with all data and (B) without high-leverage points. Values of the fitted parameters for each predictor combination and model performance estimated using Akaike’s information criterion (AIC). Model outputs for each combination of predictors. We calculated Akaike’s weights for model averaging following Burnham & Anderson [57]. Additional file 4: Invasion costs (total costs and highly reliable, observed costs) for European Union member states recorded in InvaCost v4.1, in 2017 US$ billion. Additional file 5: Comparison of the number of established alien species in the European Union and alien species in InvaCost v4.1. Additional file 6. Established alien species of Union concern recorded among the established alien species in the European Union with the first European Union member state they were recorded in and the year of first record [48]. Additional file 7: Breakdown of interpolated costs excluding high-leverage points. Additional file 8: Country-level costs recorded in InvaCost with and without high-leverage points and the respective projected additional cost and percent increase. Additional file 9: Country-level costs recorded in InvaCost by type of cost (a) and impacted sector (b) with and without extreme values and the respective projected additional cost and percent increase. Additional file 10: Temporal projection of total annual management costs (a), recorded species per year with management costs (b), and number of reported references on management expenditure in InvaCost v4.1 per year (c) using linear (left, in blue) and quadratic (right, in orange) robust regressions and their respective confidence intervals. Solid dots and lines represent trends without the inclusion of extreme values. Open circles and dashed lines represent the respective trends when including all data (i.e., including extreme values). Grey dots present data for the period 1960–1979 that are not considered in the projection due to an absence of repeated measures of individual cost entries.
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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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.789 | 0.149 |
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".