Risk screening of non-native freshwater fishes at the frontier between Asia and Europe: first application in Turkey of the fish invasiveness screening kit
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The aim of the present study was to assess the invasive potential of introduced non-native and translocated fishes in Turkey (Anatolia and Thrace) by applying the Fish Invasiveness Screening Kit (FISK), a risk identification tool for freshwater fishes. From independent evaluations by two assessors of 35 species, calibration of FISK for Turkey identified a threshold score of 23, which reliably distinguished between potentially invasive (high risk) and potentially non-invasive (medium to low risk) fishes for Anatolia (Asia) and Thrace (Europe). No species was categorized as ‘low risk’, 18 species were categorized as ‘medium risk’ and 17 as ‘high risk’ (two being ‘moderately high risk’, nine ‘high risk’, and six ‘very high risk’). The highest scoring species was gibel carp Carassius gibelio, whereas the lowest scoring species was Caucasian dwarf goby Knipowitschia caucasica, a translocated species. Assessor certainty in their responses averaged overall between ‘mostly uncertain’ and ‘mostly certain’, with red piranha Pygocentrus nattereri and topmouth gudgeon Pseudorasbora parva achieving the lowest and highest certainty values, respectively, and with overall significant differences in certainty between assessors. The results of the present study indicate that FISK is a useful and viable tool for identifying potentially invasive non-native fishes in Turkey, a country characterized by natural biogeographical frontiers.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it