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Record W2030303554 · doi:10.1364/boe.5.000701

Law of cooling, heat conduction and Stefan-Boltzmann radiation laws fitted to experimental data for bones irradiated by CO2 laser

2014· article· en· W2030303554 on OpenAlexaff
Luc Lévesque

Bibliographic record

VenueBiomedical Optics Express · 2014
Typearticle
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsThermal conductionAtmospheric temperature rangeLawThermodynamicsRate equationBoltzmann constantRange (aeronautics)Heat equationMaterials sciencePhysicsMechanicsClassical mechanicsKineticsQuantum mechanics

Abstract

fetched live from OpenAlex

The rate of cooling of domesticated pig bones is investigated within the temperature range of 20°C-320°C. Within the afore-mentioned temperature range, it was found that different behaviors in the rate of cooling were taking place. For bones reaching a temperature within the lower temperature range of 20°C-50°C, it was found that the rate of cooling is mostly governed by the empirical Newton's law of cooling. It is also shown that a transition is taking place somewhere within 50°C-100°C, where both the heat conduction equation and Newton's law apply. As bones can be raised at a fairly high temperature before burning, it was found that the rate of cooling within the range 125°C-320°C is mostly behaving according to the heat conduction equation and Stefan-Boltzmann radiation law. A pulsed CO2 laser was used to heat the bones up to a given temperature and the change of temperature as a function of time was recorded by non-contact infrared thermometer during the cooling period.

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)0.003
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.030
GPT teacher head0.332
Teacher spread0.302 · 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

Citations27
Published2014
Admission routes1
Has abstractyes

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