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Record W2053478260 · doi:10.1126/stke.2001.103.pe33

Cell Signalling - The Proteomics of It All

2001· article· en· W2053478260 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience s STKE · 2001
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsMuscular Dystrophy CanadaLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
Fundersnot available
KeywordsComputational biologyProteomicsDNA microarrayBiologySignallingResource (disambiguation)Data scienceComputer scienceGeneGene expressionGeneticsCell biology

Abstract

fetched live from OpenAlex

A challenge for biomedical scientists today is to arrive at an understanding of cellular behavior on a global scale. The advent of DNA microarrays has greatly facilitated discovery of gene expression profiles associated with different cellular states. The problem of understanding cellular signaling at the level of the interacting proteins is in some ways more challenging. Ashman et al. discuss the current methods available for studying protein interactions on a global scale, as well as directions for the future. Technical hurdles exist at many stages, from the isolation of protein complexes, to the determination of their composition, to the software and databases needed to analyze the results of large-scale, high-throughput datasets. Ashman et al. suggest that, with advances in technology and cooperation among academia and industry, a global protein interaction map that underlies cellular behavior will emerge as an essential resource for basic and applied research.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.183

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.296
Teacher spread0.273 · 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