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Record W4401092673 · doi:10.14300/mnnc.2024.19023

The outcomes of employing a specialized algorithm for forecasting and comprehensive prevention of purulent-destructive diseases affecting the chest wall in cardiothoracic surgery

2024· article· en· W4401092673 on OpenAlexaff
D Andréév, Arthur Aidemirov

Bibliographic record

VenueMedical news of the North Caucasus · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsMedicineCardiothoracic surgeryChest surgeryIntensive care medicineThoracic wallSurgeryRadiology

Abstract

fetched live from OpenAlex

РЕЗУЛЬтАтЫ пРИмЕНЕНИЯ СпЕЦИАЛИЗИРОВАННОГОАЛГОРИтмА пРОГНОЗИРОВАНИЯ И кОмпЛЕкСНОЙ пРОФИЛАктИкИ ГНОЙНО-ДЕСтРУктИВНЫХ ЗАбОЛЕВАНИЙ ГРУДНОЙ СтЕНкИ В кАРДИОтОРАкАЛЬНОЙ ХИРУРГИИ Д. Ю

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)0.003
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 score0.393
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.038
GPT teacher head0.315
Teacher spread0.277 · 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
Published2024
Admission routes1
Has abstractyes

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