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Record W7017491119

Assistir Belfast (2022) Dublado Filme Online HD Grátis |PT

2022· other· pt· W7017491119 on OpenAlexaboutno aff

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2022
Typeother
Languagept
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAdventureNorthern ireland
DOInot available

Abstract

fetched live from OpenAlex

Assistir Belfast (2022) Dublado Filme Online HD Grátis |PT ▷ https://pt-777270-belfast.tumblr.com Título: Belfast Gênero: Action, Adventure País: United States of America Estúdio: Columbia Pictures, Atlas Entertainment, PlayStation Productions, Naughty Dog, Arad Productions Fundida: Tom Holland, Mark Wahlberg, Antonio Banderas, Sophia Ali, Tati Gabrielle, Steven Waddington visão global:Na Irlanda do Norte, o garotinho Buddy (Jude Hill) e sua família da classe trabalhadora vivenciam os conflitos da década de 1960. Enquanto brinca em meio às paisagens destruídas e a violência extrema, o menino sonha com um futuro melhor. Enquanto a sua mudança de vida não acontece, ele se consola com as histórias maravilhosas contadas por Pa (Jamie Dornan), Ma (Caitríona Balfe) e seus queridos avós (Judie Dench e Ciarán Hins). Grande vencedor do Festival de Toronto 2021.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Other · Consensus signal: Other
Teacher disagreement score0.100
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.9000.766

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 head0.017
GPT teacher head0.264
Teacher spread0.247 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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
Published2022
Admission routes1
Has abstractyes

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