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Record W3112512222

Screeningul tumorilor digestive în perioada pandemiei de COVID-19

2020· article· ro· W3112512222 on OpenAlexaboutno aff
Danusia Onișor, Alina Boeriu, Olga Brusnic, Daniela Dobru

Bibliographic record

VenueMedic ro · 2020
Typearticle
Languagero
FieldMedicine
TopicMultiple and Secondary Primary Cancers
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicMedicineCoronavirus disease 2019 (COVID-19)Incidence (geometry)Cancer2019-20 coronavirus outbreakQuarter (Canadian coin)DiseaseVirologyInternal medicineOutbreakGeographyInfectious disease (medical specialty)
DOInot available

Abstract

fetched live from OpenAlex

The COVID-10 pandemic has slowed the pace of our lives in all aspects, temporarily halting screening and prophylaxis measures in every area, including health. Gastrointestinal (GI) cancers account for more than a quarter (26%) of the overall incidence of cancer and more than a third (35%) of all cancer deaths, which is why sustained efforts are needed to detect these neoplasms in situ, or even the discovery of the related precursors. Therefore, the resumption of screening programs and the recovery of the delayed period represent an extremely important and necessary objective.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.066
GPT teacher head0.326
Teacher spread0.260 · 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 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
Published2020
Admission routes1
Has abstractyes

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