New Mineral Names
Bibliographic record
Abstract
The gCube System - SDMX Registry client library -------------------------------------------------- SDMX Registry Client API and implementation for interacting with SDMX Fusion Registry. It provides methods for submitting and retrieving a subset of structural metadata described in the SDMX standards. This software is part of the gCube Framework (https://www.gcube-system.org/): an open-source software toolkit used for building and operating Hybrid Data Infrastructures enabling the dynamic deployment of Virtual Research Environments by favouring the realisation of reuse oriented policies. The projects leading to this software have received funding from a series of European Union programmes including: * the Sixth Framework Programme for Research and Technological Development - DILIGENT (grant no. 004260); * the Seventh Framework Programme for research, technological development and demonstration - D4Science (grant no. 212488), D4Science-II (grant no. 239019),ENVRI (grant no. 283465), EUBrazilOpenBio (grant no. 288754), iMarine (grant no. 283644); * the H2020 research and innovation programme - BlueBRIDGE (grant no. 675680), EGIEngage (grant no. 654142), ENVRIplus (grant no. 654182), Parthenos (grant no. 654119), SoBigData (grant no. 654024); Version -------------------------------------------------- 3.0.2-4.1.1-130755 (2016-12-15) Please see the file named "changelog.xml" in this directory for the release notes. Authors -------------------------------------------------- * Luigi Fortunati (luigi.fortunati-AT-isti.cnr.it), CNR Pisa, Istituto di Scienza e Tecnologie dell'Informazione "A. Faedo". Maintainers ----------- * Luigi Fortunati (luigi.fortunati-AT-isti.cnr.it), CNR Pisa, Istituto di Scienza e Tecnologie dell'Informazione "A. Faedo". Download information -------------------------------------------------- Source code is available from SVN: https://svn.research-infrastructures.eu/public/d4science/gcube/trunk/data-publishing/sdmx-registry-client/ Binaries can be downloaded from the gCube website: https://www.gcube-system.org/ Installation -------------------------------------------------- Installation documentation is available on-line in the gCube Wiki: https://wiki.gcube-system.org/gcube/index.php/GCube_SDMX_Statistical_Data_Dissemination_System Documentation -------------------------------------------------- Documentation is available on-line in the gCube Wiki: https://wiki.gcube-system.org/gcube/index.php/GCube_SDMX_Statistical_Data_Dissemination_System Support -------------------------------------------------- Bugs and support requests can be reported in the gCube issue tracking tool: https://support.d4science.org/projects/gcube/ Licensing -------------------------------------------------- This software is licensed under the terms you may find in the file named "LICENSE" in this directory.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.474 | 0.356 |
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".