Mapping Plastic Greenhouses With LANDSAT 8 Imagery in Valparaiso, Chile
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
In the last decades there has been a strong increase around the world in the use of plastic greenhouses (PGs). The Valparaíso region, in the central valley of Chile, has not been the exception, and the area covered by greenhouses has also experienced an increase over the years, reaching 1180 ha in 2007. Taking into account that agriculture in this region employs more than 60,000 people and accounts for 4% of the regional GDP, this information should be available to be included in territorial planning and incorporated into hydrological, economic, and food security models. To do this, the authors propose a new method for identifying the surface covered by PGs based on the intersection of the normalized difference indices and the areas excluded by the masks. The results showed that this methodology was able to identify with a general precision of 86.25% which allowed to classify 1409.85 ha. This area is consistent with the agricultural census carried out in 2007 and with the increase of more than 900 subsidies granted by the government for the installation of new structures.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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