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Record W3208101745 · doi:10.5281/zenodo.1164584

Mad Twinnet Pre-Trained Weights

2018· article· en· W3208101745 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

VenuearXiv (Cornell University) · 2018
Typearticle
Languageen
FieldComputer Science
TopicAge of Information Optimization
Canadian institutionsUniversité de MontréalConcordia University
Fundersnot available
KeywordsComputer scienceRemote sensingGeology

Abstract

fetched live from OpenAlex

This is a .zip file containing the SDR, SIR, and SAR results (per file) of the MaD TwinNet, evaluated on the Test subset of the Demixing Secret Dataset (DSD). Each file in the .zip archive, is a file containing the evaluation results of the MaD TwinNet method. The results have been serialized (i.e. saved to the hard disk) using the Python 3.6v pickle package and <pre><code class="language-python">protocol=2</code></pre> The order of the results for each metric, is the same as the order of the evaluation files at the DSD. This means that each result file, contains a list of arrays (the arrays are bumpy ndarrays). <strong>Note bold:</strong> The LICENSE of the code of the MaD TwinNet applies also to these results.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.964
Threshold uncertainty score0.847

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.029
GPT teacher head0.162
Teacher spread0.133 · 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