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Record W2800391420 · doi:10.24875/j.gamo.m18000105

Mortalidad por Cáncer en México: actualización 2015

2018· article· es· W2800391420 on OpenAlexaff
Fernando Aldaco-Sarvide, Perla Pérez-Pérez, María G. Cervantes-Sánchez, Laura Torrecillas-Torres, Aura Argentina Erazo-Valle-Solís, Paula Cabrera‐Galeana, Daniel Motola‐Kuba, Pablo Anaya, Samuel Rivera, Eduardo Cárdenas-Cárdenas

Bibliographic record

VenueGaceta Mexicana de Oncología · 2018
Typearticle
Languagees
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsInstitute of Cancer Research
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Introduccin: El cncer es una de las principales causas de mortalidad en Mxico y se espera que su tasa aumente en los prximos aos, principalmente debido al envejecimiento de la poblacin; sin embargo, pocos estudios exhaustivos evaluando la mortalidad por cncer se han publicado recientemente. Objetivo: Proporcionar una actualizacin

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient 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: Empirical
Teacher disagreement score0.164
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.006

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 head0.057
GPT teacher head0.479
Teacher spread0.422 · 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

Citations15
Published2018
Admission routes1
Has abstractyes

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