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Record W2356491261

A Historical Survey:The birth of Hilbert space

2013· article· en· W2356491261 on OpenAlexaff
LI Yay

Bibliographic record

VenueZiran bianzhengfa yanjiu · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum Mechanics and Applications
Canadian institutionsScience North
Fundersnot available
KeywordsRigged Hilbert spaceHilbert spaceProjective Hilbert spaceMathematical formulation of quantum mechanicsMathematicsPerspective (graphical)Space (punctuation)POVMHilbert manifoldReproducing kernel Hilbert spaceVon Neumann architectureSIC-POVMHilbert–Poincaré seriesPure mathematicsDevelopment (topology)Mathematical analysisQuantum statistical mechanicsQuantumQuantum mechanicsLinguisticsPhysicsPhilosophyQuantum dynamicsGeometryQuantum operation
DOInot available

Abstract

fetched live from OpenAlex

Hilbert space is an important content of functional analysis and quantum mechanics. The idea of Hilbert space stems from Hilbert 's works on integral equation, but soon was given concrete forms by Hilbert's followers. To satisfy the need for the development of quantum mechanics and follow the trend of development of structural mathematics in the 20th century, John von Neumann defined abstract Hilbert space axiomatically. The his-torical exploring on the origin and evolution of Hilbert space not only help us to better understand the theory of Hilbert space and the history of func-tional analysis, but also provide a significant perspective to reveal the links between mathematics and physics.

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)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.006
Science and technology studies0.0020.005
Scholarly communication0.0030.007
Open science0.0010.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0070.002

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 head0.020
GPT teacher head0.228
Teacher spread0.208 · 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
GenreReview

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
Published2013
Admission routes1
Has abstractyes

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