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Record W4212857293 · doi:10.5539/apr.v14n1p1

‘Kinetic Energy’ (I): On the Physical Meaning of the Product mv2: The Experiments of G. Poleni and of J. W. ‘sGravesande

2022· article· en· W4212857293 on OpenAlexvenueno aff
Giancarlo Cavazzini

Bibliographic record

VenueApplied Physics Research · 2022
Typearticle
Languageen
FieldEngineering
TopicMechanics and Biomechanics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsKinetic energyPhysicsAction (physics)GravitationRest (music)Potential energyMechanical energyClassical mechanicsRest frameProduct (mathematics)MechanicsPower (physics)ThermodynamicsGeometryMathematicsQuantum mechanics

Abstract

fetched live from OpenAlex

The results of renowned experimental works of Giovanni Poleni in 1718 and of Jakob W. ‘sGravesande in 1722 suggest that the ‘energy of motion’ or ‘kinetic energy’ of a material body which is moved in a vacuum in a reference frame by a gravitational process is proportional to the ’mass’ of the body and to the velocity of the body in the reference frame, and not to the mass and to the square of the velocity. Consequently, the amount of mechanical energy which is expended by gravitation in moving a body in a vacuum over a vertical distance z is not, as is currently believed, proportional to this distance, but it is proportional to the time-span of action of the process. The product between the mass of the body and the square of the velocity of the body is not proportional only to the amount of mechanical energy of motion of the body moved by the gravitational process, but it is proportional also to the power with which such an amount of ‘kinetic energy’ is consumed by collision with a plastic target at rest in the reference frame.

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)0.001
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.011
Scholarly communication0.0030.008
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.002

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 head0.057
GPT teacher head0.292
Teacher spread0.235 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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