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Record W2738589440 · doi:10.2298/mpns1706183b

Branislav Nusic and X-rays in the story “Roentgen’s Photography”

2017· article· en· W2738589440 on OpenAlexaff
Rade Babic, Ankica Jelenković, Gordana Stanković-Babić, Strahinja Babic

Bibliographic record

VenueMedicinski pregled · 2017
Typearticle
Languageen
FieldMedicine
TopicRadiology practices and education
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsSerbianMedicineClassicsVisual artsHistoryArtPhilosophyLinguistics

Abstract

fetched live from OpenAlex

Introduction. Shortly after the discovery of X-rays, their practical application in the clinical practice became the object of interest of many non-medical individuals. One of them was the famous Serbian writer, Branislav Nusic. This paper presents the life and work of Branislav Nusic, as well as his article: ?Roentgen?s Photography? which was published in the journal ?Politics? (July 8, 1906; N? 892, p. 3), under the alias Ben Akiba, in the Cyrillic script. The life and work of Branislav Nusic. Alchiviadi Nu?a, later Branislav Nusic (1864 - 1938) was a great Serbian literate, playwright, journalist, photographer, politician, diplomat, member of the Serbian Royal Academy, President of the Association of Yugoslav Playwrights, manager of the theaters in Belgrade, Novi Sad, Skopje and Sarajevo, and a military volunteer in the Serbian - Bulgarian war (1885). ?Roentgen?s Photography?. The author wrote this text in his own way, the only way he could and knew, vividly and wittily. He knew about the great power and strength of X-ray radiation, and he wrote of his knowledge in this short story. Without Branislav Nusic, the history of Serbian radiology would be poorer for not seeing the X-rays by the eyes of an educated, intelligent and, above all, humorous writer. Conclusion. Branislav Nusic, alongside Nikola Tesla, Mihajlo Pupin Idvorski, Dr. Abraham Vinaver, and all past and present Serbian radiologists, has become an essential and memorable link in the chain of the history of the Serbian radiology.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.335
Teacher spread0.304 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2017
Admission routes1
Has abstractyes

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