MétaCan
Menu
Back to cohort
Record W4214489000 · doi:10.3103/s0147688221040043

The Library in the Information Ecosystem of Open Science

2021· article· en· W4214489000 on OpenAlexfundno aff
N. S. Redkina

Bibliographic record

VenueScientific and Technical Information Processing · 2021
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesNational Cancer InstituteNational Heart, Lung, and Blood InstituteNational Institutes of HealthFundamental Research Funds for the Central UniversitiesNational Research Foundation of KoreaMedical Research CouncilConselho Nacional de Desenvolvimento Científico e TecnológicoJapan Society for the Promotion of ScienceHorizon 2020 Framework ProgrammeMinistry of Education, Culture, Sports, Science and TechnologyMinistry of Science and Technology of the People's Republic of ChinaU.S. Department of Health and Human ServicesMinistry of Education of the People's Republic of ChinaU.S. Department of EnergyNational Natural Science Foundation of ChinaEuropean Regional Development FundU.S. Department of DefenseEuropean CommissionDeutsche ForschungsgemeinschaftGovernment of CanadaUK Research and InnovationNational Science FoundationNational Key Research and Development Program of ChinaNational Research FoundationEngineering and Physical Sciences Research Council
KeywordsOpen scienceField (mathematics)Computer scienceEcosystemData scienceWorld Wide WebKnowledge managementEcologyBiologyMathematics

Abstract

fetched live from OpenAlex

The results of an analysis of trends in the development of the information ecosystem of open science based on the study of the global document flow, open access resources, and scientific data repositories, as well as initiatives in the field of open science, including during the COVID-19 pandemic, are presented. The directions of activity of libraries in these conditions are determined.

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 imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.999
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.029
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0130.030
Science and technology studies0.0120.013
Scholarly communication0.0550.047
Open science0.0010.018
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0120.003

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 head0.050
GPT teacher head0.341
Teacher spread0.292 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueScientific and Technical Information ProcessingSame topicResearch Data Management PracticesFrench-language works237,207