Diptera diversity in fifteen urban green spaces of a southern temperate city
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
We collected the data for a project with the broad objective of studying urbanization effects on arthropod communities. Dipterans were collected from vegetation with a G-VAC (aspirator) in 15 urban green patches in Córdoba city, Argentina, during the summer (February) and winter (July-August) of 2014, diurnally within 9 am - 5 pm. A Sthil® vacuum cleaner with a 110 cm long and 12 cm wide tube was used to suck during 1 minute the vegetation within a square meter area (one subsample). Ten subsamples (5 at ground level and 5 up to 200 cm above the ground) were collected and pooled per site and sampling season. The pooled material collected from one site and season was considered as one sample unit (site) for data analysis. Samples were always collected on vegetation patches, which may include relatively small patches of bare ground, but not from bare ground <i>per se</i>. The minimum spatial distance between two subsamples was approximately 10 m. All adult Diptera were counted and identified to family based on morphological characteristics, mainly using taxonomic keys in McAlpine et al. (1981). (McAlpine J, Peterson B, Shewell G, Teskey H, Vockeroth J, Wood D (1981) Manual of Nearctic Diptera Vol I. Minister of Supply and Services Canada. Ottawa, Canada.)
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.346 | 0.053 |
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