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Record W2563980006 · doi:10.1139/as-2016-0050

Biodiversity databases in Russia: towards a national portal

2016· article· en· W2563980006 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueArctic Science · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
FundersDivision of Arctic SciencesLobachevsky State University of Nizhny NovgorodTomsk State University
KeywordsDatabaseUploadBiodiversityInterface (matter)Computer scienceWorld Wide WebData administrationGeographyDatabase designEcologyDatabase schema

Abstract

fetched live from OpenAlex

Russia holds massive biodiversity data accumulated in botanical and zoological collections, literature publications, annual reports of natural reserves, nature conservation, and monitoring study project reports. While some data have been digitized and organized in databases or spreadsheets, most of the biodiversity data in Russia remain dormant and digitally inaccessible. Concepts of open access to research data is spreading, and the lack of data publishing tradition and of use of data standards remain prominent. A national biodiversity information system is lacking and most of the biodiversity data are not available or the available data are not consolidated. As a result, Russian biodiversity data remain fragmented and inaccessible for researchers. The majority of Russian biodiversity databases do not have web interfaces and are accessible only to a limited numbers of researchers. The main reason for lack of access to these resources relates to the fact that the databases have previously been developed only as a local resource. In addition, many sources have previously been developed in the desktop database environments mainly using MS Access and, in some cases, earlier DBMS for DOS, i.e., file-server system, which does not have the functionality to create access to records through a web interface. Among the databases with a web interface, a few information systems have interactive maps with the species occurrence data and systems allowing registered users to upload data. It is important to note that the conceptual structures of these databases were created without taking into account modern standards of the Darwin Core; furthermore, some data sources were developed prior to the first work version of the Darwin Core release in 2001. Despite the complexity and size of the biodiversity data landscape in Russia, the interest in publishing data through international biodiversity portals is increasing among Russian researchers. Since 2014, institutional data publishers in Russia have published about 140 000 species occurrences through gbif.org. The increase in data publishing activity calls for the creation of a GBIF node in Russia, aiming to support Russian biodiversity experts in international data work.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0540.003

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.

Opus teacher head0.054
GPT teacher head0.280
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it