MétaCan
Menu
Back to cohort

Seleção genética de embriões: a melhora genética em seres humanos e sua limitação jurídica

2019· dissertation· pt· W3048773314 on OpenAlexaff
José Geraldo Romanello Bueno

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPhilosophyBiologyHumanities

Abstract

fetched live from OpenAlex

Este trabalho estuda o diagnóstico genético pré-implantacional (DGP) de embriões realizado em clínicas de reprodução assistida nos programas de fertilização in vitro e injeção intracitoplasmática, comportando certa complexidade legal; consequentemente, podendo apresentar diversos conflitos entre o casal e a clínica de reprodução.Talvez sejam as técnicas de reprodução assistida o ramo da medicina que comporta mais implicações sociais, éticas e morais.Somente na América do Sul foram realizados 18.500 casos de fertilização in vitro em um intervalo de quatro anos.No Brasil, entretanto, ainda não existe uma lei que regulamente o embrião e as técnicas de reprodução assistida, cabendo ao

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)0.004
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.344
Teacher spread0.305 · 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
GenreOther

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
Published2019
Admission routes1
Has abstractyes

Explore more

Same topicReproductive Health and TechnologiesFrench-language works237,207