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Record W4387411571 · doi:10.2478/mgr-2023-0016

In memory of Stanislav Martinát (1976–2023)

2023· article· en· W4387411571 on OpenAlexaff
Bohumil Frantál, Stephan Bartke, Justyna Chodkowska‐Miszczuk, Oleg Golubchikov, Bryn Greer‐Wootten, Pavel Klapka, Petr Klusáček, Robert Krzysztofik, Marián Kulla, Miroslava Ondráčková, Martin J. Pasqualetti, Dan van der Horst

Bibliographic record

VenueMoravian Geographical Reports · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsYork University
Fundersnot available
KeywordsCzechGeographerBusiness managementWork (physics)Library scienceHistoryPolitical scienceManagementSociologyEconomic historyEngineeringGeographyBusinessComputer scienceEconomicsBusiness administrationPhilosophyCartography

Abstract

fetched live from OpenAlex

Abstract On Sunday, August 13, 2023, Stanislav Martinát – a respected Czech geographer and member of the Editorial Board of Moravian Geographical Reports journal – died after a short serious illness at the age of 47. Despite his relatively young age, Stanislav Martinát was one of the most productive and the most cited Czech geographers. He is the author or coauthor of over 100 peer-reviewed articles, of which more than 70 were published in journals indexed in the Web of Science database. This article is a collection of personal memories from people from different workplaces from several countries who had the opportunity to work with Stanislav (Standa) and to share a part of their life stage with him.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0160.011

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 head0.019
GPT teacher head0.302
Teacher spread0.283 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations1
Published2023
Admission routes1
Has abstractyes

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