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Record W3039818129 · doi:10.1017/s1431927600033869

Insulin Receptor: Structure Via 3D EM Reconstruction, Crystallography and NMR Reveals Details of Ligand Binding and Mechanism of Transmembrane Signalling

2000· article· en· W3039818129 on OpenAlexaff
F.P. Ottensmeyer, R Z Luo, Daniel R. Beniac, Allan Fernandes, Christopher Yip

Bibliographic record

VenueMicroscopy and Microanalysis · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsIcosahedral symmetryMacromoleculeCrystallographySymmetry (geometry)MoleculeElectron microscopeChemical physicsSingle particle analysisNoise (video)Molecular physicsLigand (biochemistry)BiophysicsMaterials scienceChemistryPhysicsOpticsReceptorComputer scienceBiologyMathematicsBiochemistryImage (mathematics)Artificial intelligenceQuantum mechanicsGeometry

Abstract

fetched live from OpenAlex

Abstract For over 25 years a major effort in electron microscopy of macromolecules has been the determination of the three dimensional structure from the two-dimensional electron micrographs of such specimens. Great success has been realized when the macromolecule or complex takes the form of an array such as a 2D crystal (1,2), a helical structure (3,4) or one with icosahedral symmetry (5,6). However, for molecules which do not form such arrays, and in the limit only exist as single particles, a number of challenges have had to be addressed. No easy averaging of noisy low dose images is possible due to the lack of lateral and rotational symmetry. Random unknown orientations of the particles have to be determined, a process exacerbated by noise if low dose images are used as input. Alternatively, higher dose images result in radiation-induced structural alterations of the macromolecule.

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 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 score0.022
Threshold uncertainty score0.880

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 science0.0000.000
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 head0.003
GPT teacher head0.205
Teacher spread0.202 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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
Published2000
Admission routes1
Has abstractyes

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