MétaCan
Menu
Back to cohort
Record W6888924613 · doi:10.24433/co.9905505.v2

Quantum Field Lens Coding Software for System State Simulation, Strong Prediction and Game Application

2024· other· en· W6888924613 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCode Ocean · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsUploadSoftwareDebuggingPython (programming language)File formatData fileCode (set theory)Source codeFile sizeDirectory

Abstract

fetched live from OpenAlex

This software program (QFLCS) analyzes the measurement outcome probability (P) data from datasets generated by Quantum Double-field (QDF) Circuits. The datasets are compared between ES and GS states as a P indicator generated for measurement samples. Small dataset samples denote: a. A particle pair’s energy state in a QDF, superposing between QDF points (sublevels of a GS, or see Table 2 in Sec. 3 of the published article), b. a single field (SF or particle state), an ES relative to a GS from (a.), prior to its transform into a QDF, c. the expected transformation of fields (ES ←→GS) and their ⟨M(P, ψ_ij)⟩, as in Sec. 3 of the published article. The file structure here is a mirror of the Mendeley repository file structure of v3+ at https://data.mendeley.com/datasets/gf2s8jkdjf/3, but with a smaller file size for efficient download and use of the QFLCA project's code and documentation (website). Certain small updates have been made in the main python file uploaded here on Code Ocean for minor debugging purposes. * The main file is which imports and executes the or QDF-LCode_IBMQ-2024.py code for the simulation under Win OS or Linux OS. * We recommend downloading the entire directory according to the folder structure and run QAI-LCode_QFLCC.py in VSC with python latest packages installed for windows OS (the QDF game is developed for Windows OS, yet parts of the code for sound and display can be rewritten for Linux OS), e.g. "winsound" package as a compatible option. Other packages are needed to be installed, or code rewritten for "sound" and "display" compatibility under other operating systems. * The QAI-LCode_QFLCC.py file has a Pygame GUI and other packages suited for local machine runs, rather than running this file on the Code Ocean platform which could take hours to compile and run a compatible program/game with packages. However, the QDF-LCode_IBMQ-2024-codable.py can be run here as the core of the simulation program simulating the QDF circuit. A short presentation explaining these points are given in the directory as the "QAI-COcean-Demo.mp4" file. * The User and Developer’s documentation/manual/demo is found under the directory, as and contents. * In each folder, , , and under , Tips.txt and/or ReadMe.txt files exist to explain the contents of that directory. Also, under directory, a ReadMe file exists explaining the manual computation and presentation parts of the project.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.953
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 integrity0.0000.000
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 head0.026
GPT teacher head0.286
Teacher spread0.259 · 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

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCode OceanFrench-language works237,207