Biopotential and chemical characterization of extracts and essential oils of species from Juniperus L. genus (Cupressaceae).
Bibliographic record
Abstract
Prirodno-matematički fakultet Departman za hemiju, biohemiju i zaštitu životne sredine Eksperimentalni deo ove doktorske disertacije urađen je u laboratoriji za biohemiju lekovitog bilja na Departmanu za hemiju, biohemiju i zaštitu životne sredine Prirodnomatematičkog fakulteta, Univerziteta u Novom Sadu, u okviru realizacije projekata Ministarstva prosvete i nauke Republike Srbije br.142036 i 172058.Dugujem duboku zahvalnost svom mentoru prof.dr Nedi Mimici-Dukić, na pruženoj prilici da učim i radim ono što volim, dragocenim, ljudskim i stručnim savetima i pomoći tokom celog mog studiranja i rada.Zahvaljujem se prof.dr Kseniji Kuhajdi za svu podršku i interesovanje za moj rad.Posebnu zahvalnost dugujem docentu dr Ivani Beari na svesrdnoj pomoći, brojnim idejama i sugestijama u planiranju, izveđenju eksperimentalnog dela i pisanju teze, a iznad svega na iskrenom prijateljstvu.Za izbor, sakupljanje i determinaciju biljnog materijala, korisne savete i pomoć tokom izrade ove teze, veliku zahvalnost dugujem docentu dr Biljani Božin i docentu dr Goranu Anačkovu.Zahvaljujem se docentu dr Dejanu Orčiću, Emiliji Jovin, mr Nataši Simin, Kristini Balog i Marini Francišković za svakodnevnu pomoć i veliku podršku tokom rada.Od velikog značaja bila mi je saradnja sa docentom dr Petrom Kneževićem u izvođenju i analizi antimikrobnih testova, na čemu mu se toplo zahvaljujem.Hvala zdravstvenim radnicima sa Instituta za transfuziju krvi Vojvodine na ustupljenim preparatima trombocita.Hvala Ružici Marušić, Jovani Francuz i Sanji Dožić na velikom prijateljstvu tokom studiranja i rada, a svim zaposlenima na Departmanu za hemiju, biohemiju i zaštitu životne sredine na pomoći i kolegijalnosti.Hvala svim mojim studentima na velikoj pomoći.Đorđiju hvala na nesebičnom razumevanju, a svim prijateljima na prijateljstvu.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".