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Record W6969332549 · doi:10.5683/sp3/s1t3x8

ARCA Finder

2023· dataset· en· W6969332549 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsMcGill University
Fundersnot available
KeywordsSoftwarePoint (geometry)Graphical user interfacePosition (finance)Frame (networking)Listing (finance)

Abstract

fetched live from OpenAlex

---------------------------- IMPORTANT ---------------------------- ARCA Finder software is to be used solely for non-commercial and/or academic purposes! The ARCA Finder presents a novel software and graphical user interface which aids the user in efficiently determining advancing and receding contact angles from a table of data listing contact angle and contact point versus video frame number. The software considers the full definition of an advancing and receding contact angle to guide the user to meaningful changes in contact point position and contact angles maxima/minima. Furthermore, the GUI allows for facile comparison of left and right droplet behaviour, and inspection of individual video frames to determine erroneous data. For further information on ARCA Finder, please refer to the associated journal publication and/or contact anne.kietzig@mcgill.ca

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)0.002
metaresearch head score (Gemma)0.011
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.125
Threshold uncertainty score0.419

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.008
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0040.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1250.238

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 head0.039
GPT teacher head0.304
Teacher spread0.265 · 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
GenreDataset

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
Published2023
Admission routes2
Has abstractyes

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Same venueBorealisFrench-language works237,207