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Record W4241897296 · doi:10.1016/s1359-6128(05)00727-5

Alfa Laval AB, Sweden

2005· article· en· W4241897296 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePump Industry Analyst · 2005
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsnot available
Fundersnot available
KeywordsFragment molecular orbitalComputationElectronic correlationMassively parallelPerturbation theory (quantum mechanics)Hemagglutinin (influenza)PhysicsPerturbation (astronomy)Molecular orbitalComputational chemistryComputational scienceComputer scienceChemistryParallel computingMoleculeAlgorithmAntigenBiologyGeneticsQuantum mechanics

Abstract

fetched live from OpenAlex

The fragment molecular orbital (FMO) calculations have been successfully applied to a variety of realistic biochemical problems, by using our original Abinit-mp program. In these applications, the inclusion of electron correlation through the second-order Møller-Plesset perturbation (MP2) was demonstrated to be essential to obtain qualitatively correct descriptions. Recently, the FMO calculations in Abinit-mp were tuned for a massively parallel-vector processing. A series of FMO-MP2/6-31G calculations were performed on the Earth Simulator by which up to 4096 vector processors are available. The largest FMO-MP2 computation was carried out for an influenza hemagglutinin antigen–antibody system consisting of 921 residues, which was completed within one hour with 4096 processors.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score1.000

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.044
GPT teacher head0.351
Teacher spread0.307 · 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