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Record W4386463014 · doi:10.1007/978-1-0716-3393-9

SH2 Domains

2023· book· en· W4386463014 on OpenAlexfundno aff
Teresa Carlomagno, Maja Köhn

Bibliographic record

VenueMethods in molecular biology · 2023
Typebook
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsnot available
FundersUniversidade Estadual PaulistaUniversität LeipzigUniversidad Nacional de San MartínHigh Energy Accelerator Research OrganizationUniversity of TorontoUniversity of Illinois at Urbana-ChampaignUniversity of Toronto MississaugaUniversidade Federal do Rio de JaneiroMonash UniversityUniversität des SaarlandesChinese University of Hong KongMonash Biomedicine Discovery Institute, Monash UniversityUniversità degli Studi di Roma Tor VergataEuropean Molecular Biology LaboratoryConsejo Nacional de Investigaciones Científicas y TécnicasYale Cancer CenterYale UniversityMoffitt Cancer CenterUniversity of South FloridaUniversity of Nebraska-Lincoln
KeywordsFunction (biology)Computer scienceBiologyEvolutionary biology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
metaresearch head score (Gemma)0.000
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: Other
Teacher disagreement score0.132
Threshold uncertainty score0.441

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1320.128

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 head0.052
GPT teacher head0.448
Teacher spread0.396 · 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
Published2023
Admission routes1
Has abstractno

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