Development and optimalization of methodology for detection of GMO potatoes
Bibliographic record
Abstract
Genetically modified (GM) or transgenic crops, now more often called #x201c;Biotech crops#x201c; they are commercially cultivated since 1996. And also since 1996, the first year of commercialization of biotech crops, GM potatoes were cultivated in USA, Mexico, Canada and later in South Africa, China and India. The global area of approved biotech crops in 2006 was 102 million hectares and 22 countries grew biotech crops, 11 developing countries and 11 industrial countries. The Czech Republic is on of the six EU countries where biotech crops are cultivated at present. The most compelling case for biotechnology, and more specifically biotech crops, is their capability to contribute to: increasing crop productivity and stability of productivity and production; conserving biodiversity, as a land-saving technology; the production of renewable resource based bio-fuels. This diploma paper was focused on developing of fast, precise and cheap method based on PCR to detect the presence of transgenes in potatoes - tubers and leaves, allows monitoring the presence of GM potatoes in market, environment, etc. and to quantify #x201c;contamination#x201c; of ware potatoes (tubers) with GM ones.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".