Portuguese Polar Program Annual Report 2020
Bibliographic record
Abstract
The Portuguese Polar Program - PROPOLAR is funded by the Fundação para a Ciência e a Tecnologia ( based at Instituto de Geografia e Ordenamento do Território ( of the University of Lisbon ( The coordination of PROPOLAR is led by the Centro de Estudos Geográficos from Instituto de Geografia e Ordenamento do Território University of Lisbon (CEG/IGOT ULISBOA), under a Coordinating Committee that includes members from 4 other research centres, namely the Centro de Ciências do Mar University of Algarve (CCMAR UALG), the Centro de Ciências do Mar e do Ambiente University of Coimbra (MARE UC), the Centro de Química Estrutural from Instituto Superior Técnico University of Lisboa (CQE/IST ULISBOA), and the Centro Interdisciplinar de Investigação Marinha e Ambiental University of Oporto (CIIMAR U PORTO) Gonçalo Vieira (CEG/IGOT ULISBOA) is the Head of the program The remarkable effort and commitment of the Portuguese Polar scientists, within the framework of the International Polar Year ( 2007 08 were key to promote awareness of the importance of Polar science and research for Portugal A strategic plan encompassing three main objectives was then set out to i creating a Portuguese Polar Program focused on polar research and innovation and supporting the young generation of Polar scientists,scientists,( signing the Antarctic Treaty, and ( implementing a national Polar education and outreach program With the support of the FCT, PROPOLAR started in 2007 Portugal ratified the Antarctic Treaty in 2010 and the Madrid Protocol in 2014 and has established liaisons with major international Polar scientific and management organisations and networks PROPOLAR in close connection with the FCT, has ensured consolidation and sustainability of the development of Portuguese Polar science
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.068 | 0.056 |
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".