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Record W2761551051 · doi:10.1186/s13053-017-0074-9

Meeting abstracts from the Annual Conference on Hereditary Cancers 2015

2017· article· en· W2761551051 on OpenAlexaff
Ella R. Thompson, Michelle W. Wong‐Brown, Simone M. Rowley, S Dooley, Na Lil, Michael Hipwell, Simone McInerny, Cliff Meldrum, Lisa Devereux, David Mossman, Alison H. Trainer, Briar-Rose Millar, Gillian Mitchell, Cate Smith, Paul A. James, Ian Campbell, Rodney J. Scott, Katarzyna Klonowska, Anna Jakubowska, Jeļena Maksimenko, Arvīds Irmejs, Miki Nakazawa, Inga Melbārde-Gorkuša, Genādijs Trofimovičs, Jānis Gardovskis, Edvīns Miklaševičs, Karolina Tęcza, Jolanta Pamuła‐Piłat, Joanna Łanuszewska, Ewa Grzybowska, M. Szwiec, J. Tomiczek-Szwiec, M. Gełej, C. Cybulski, T. Huzarski, E. Kilar, Małgorzata Oczko‐Wojciechowska, Michał Świerniak, Jolanta Krajewska, Małgorzata Kowalska, Tomasz Tyszkiewicz, Agnieszka Pawlaczek, Michał Jarząb, Monika Kowal, Dagmara Rusinek, Jadwiga Żebracka‐Gala, Agnieszka Czarniecka, Barbara Jarząb, Andrzej Pławski, Paweł Boruń, Joanna Szczepinska, Monika Siołek, Beata Kozak‐Klonowska, Katarzyna Kaczmarek, Magdalena Muszyńska, Wojciech Marciniak, Grzegorz Sukiennicki, Marcin Lener, Katarzyna Durda, Katarzyna Jaworska–Bieniek, Tomasz Gromowski, Tomasz Huzarski, Tomasz Byrski, Jacek Gronwald, Oleg Oszurek, Cezary Cybulski, Tadeusz Dębniak, Antoni Morawski, Anna Jakubowska, Jan Lubiński, M.H. Post

Bibliographic record

VenueHereditary Cancer in Clinical Practice · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsBC Cancer Agency
FundersMinisterstwo Edukacji i Nauki
KeywordsMedicineHuman geneticsFamily medicineLibrary scienceGeneticsGene

Abstract

fetched live from OpenAlex

Conclusions 1) The concentration of selenium in the blood may be a marker of occurrence of age-related cataracts.2) The low selenium levels may be a risk factor for age-related cataract in the Polish population Keywords selenium, age-related cataract

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)0.002
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: none
Teacher disagreement score0.195
Threshold uncertainty score0.654

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.1950.076

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 head0.075
GPT teacher head0.430
Teacher spread0.355 · 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
Published2017
Admission routes1
Has abstractyes

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