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Record W3109777202 · doi:10.1088/1361-6404/abce1f

Experimental test of fair three-sided coins

2020· article· en· W3109777202 on OpenAlexaff
Pasquale Bosso, Anthony I. Huber, Vasil Todorinov

Bibliographic record

VenueEuropean Journal of Physics · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStatistical Mechanics and Entropy
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsSimple (philosophy)Statement (logic)PhysicsCharacterization (materials science)Experimental dataBasis (linear algebra)RADIUSTest (biology)Statistical hypothesis testingAlgorithmCalculus (dental)Theoretical physicsApplied mathematicsMathematical economicsComputer scienceEpistemologyStatisticsGeometryMathematicsOpticsComputer security

Abstract

fetched live from OpenAlex

Abstract A simple model for a fair ‘three-sided coin’ is proposed and tested. Describing the coin as a cylinder with a given height and basis radius, this model efficiently characterizes the problem, constraining the size of the coin. A statistical analysis of the data collected from actual realizations of such coins has been performed, supporting the proposed model. Besides studying the case of a fair three-sided coin, this work represents a model for an explicit application of the scientific method, in which all parts (problem characterization, statement of a hypothesis, experiment, analysis, description, conclusions) have clearly directed its development. Thus, it represents an useful illustration of such method for undergraduate students.

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)0.008
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.029
GPT teacher head0.244
Teacher spread0.215 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations1
Published2020
Admission routes1
Has abstractyes

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