MétaCan
Menu
Back to cohort
Record W3036034674 · doi:10.71781/16977

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

2020· dissertation· fr· W3036034674 on OpenAlexfundno aff
Charles Alexandre Bédard

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.

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.010
Scholarly communication0.0080.015
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.047
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

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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueOpen MINDSame topicComputability, Logic, AI AlgorithmsFrench-language works237,207