MétaCan
Menu
Back to cohort

Libros de resúmenes de los congresos científicos nacionales del Perú, 2010-2014

2021· dataset· en· W6958495092 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2021
Typedataset
Languageen
FieldEngineering
TopicCharacterization and Applications of Magnetic Nanoparticles
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Event (particle physics)CohortScientific literatureRetrospective cohort study

Abstract

fetched live from OpenAlex

Every year the National Scientific Congress (NSC) is held, an event that receives research papers from the medical students of Peru. The objective of the study was to determine the publication rate of these papers and their associated factors. A retrospective cohort study was conducted for which the abstract books of the NSC from 2010 to 2014 were reviewed. We determined the publication rate and the time in months until the publication of the work. We included 407 abstracts, of which 97 (23.8%) were published. The median time to publication was 14 months (IQR: 5-23). Almost a quarter of the papers submitted to the NSC between 2010 and 2014 were published in a scientific journal.

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)0.003
metaresearch head score (Gemma)0.032
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.045
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0110.019
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0450.030

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 head0.018
GPT teacher head0.240
Teacher spread0.222 · 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
GenreDataset

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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueFigshareSame topicCharacterization and Applications of Magnetic NanoparticlesFrench-language works237,207