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Record W3036034674 · doi:10.71781/16977

L'information algorithmique en physique : émergence, sophistication et localité quantique

2020· dissertation· fr· W3036034674 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.

fundA Canadian funder is recorded on the work.
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

VenueOpen MIND · 2020
Typedissertation
Languagefr
FieldComputer Science
TopicComputability, Logic, AI Algorithms
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaInstitut für Quantenoptik und Quanteninformation
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Cette thèse explore des aspects du monde naturel par la lentille de l'information algorithmique. La notion de l'émergence, intuitivement reliée à tant de phénomènes naturels, se voit offrir une définition cadrée dans le domaine plus spécifique des statistiques algorithmiques. Capturant toutes deux l'organisation non triviale d'un objet, la sophistication et la profondeur logique sont relativisées à un objet auxiliaire puis remises en relation. Enfin, des modèles proposant une description locale des systèmes quantiques sont démontrés équivalents, ont leur coût de description quantifié et sont généralisés aux systèmes continus.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0020.005
Open science0.0040.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.005

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 head0.047
GPT teacher head0.335
Teacher spread0.288 · 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