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Record W4400201623 · doi:10.5114/mp.2024.141059

VII Zjazd Polskiego Towarzystwa Medycyny Paliatywnej, Gdańsk, 27–29 czerwca 2024 r.

2024· article· pl· W4400201623 on OpenAlexaboutno aff
Sylwia Dosz, Marcin Kaźmirski

Bibliographic record

VenueMedycyna Paliatywna · 2024
Typearticle
Languagepl
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsnot available
Fundersnot available
KeywordsTheologyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

AMA Dosz S, Kaźmirski M. VII Zjazd Polskiego Towarzystwa Medycyny Paliatywnej, Gdańsk, 27–29 czerwca 2024 r. Medycyna Paliatywna/Palliative Medicine. 2024;16(2):129-132. doi:10.5114/mp.2024.141059. APA Dosz, S., & Kaźmirski, M. (2024). VII Zjazd Polskiego Towarzystwa Medycyny Paliatywnej, Gdańsk, 27–29 czerwca 2024 r. Medycyna Paliatywna/Palliative Medicine, 16(2), 129-132. https://doi.org/10.5114/mp.2024.141059 Chicago Dosz, Sylwia, and Marcin Kaźmirski. 2024. "VII Zjazd Polskiego Towarzystwa Medycyny Paliatywnej, Gdańsk, 27–29 czerwca 2024 r.". Medycyna Paliatywna/Palliative Medicine 16 (2): 129-132. doi:10.5114/mp.2024.141059. Harvard Dosz, S., and Kaźmirski, M. (2024). VII Zjazd Polskiego Towarzystwa Medycyny Paliatywnej, Gdańsk, 27–29 czerwca 2024 r. Medycyna Paliatywna/Palliative Medicine, 16(2), pp.129-132. https://doi.org/10.5114/mp.2024.141059 MLA Dosz, Sylwia et al. "VII Zjazd Polskiego Towarzystwa Medycyny Paliatywnej, Gdańsk, 27–29 czerwca 2024 r." Medycyna Paliatywna/Palliative Medicine, vol. 16, no. 2, 2024, pp. 129-132. doi:10.5114/mp.2024.141059. Vancouver Dosz S, Kaźmirski M. VII Zjazd Polskiego Towarzystwa Medycyny Paliatywnej, Gdańsk, 27–29 czerwca 2024 r. Medycyna Paliatywna/Palliative Medicine. 2024;16(2):129-132. doi:10.5114/mp.2024.141059.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.726
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.006
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0040.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0290.029

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 head0.034
GPT teacher head0.319
Teacher spread0.285 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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