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Record W2001775645 · doi:10.3415/vcot-14-05-0081

Influence of calibration protocols for a pressure-sensing walkway on kinetic and temporospatial parameters

2014· article· en· W2001775645 on OpenAlexaboutno aff
Felipe Stéfan Agostinho, B Geraldo, Pedro L. T. Justolin, Carlos Roberto Teixeira, F L M L Lins, Frederico Ozanan Barros Monteiro, Sheila Canevese Rahal

Bibliographic record

VenueVeterinary and Comparative Orthopaedics and Traumatology · 2014
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsnot available
FundersUniversidade Estadual PaulistaFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsMedicineCalibrationStatistics

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate the influence on the kinetic and temporospatial parameters of calibration protocols with point and step techniques for a pressure-sensing walkway. METHODS: Nine Labrador dogs were used. Two protocols of point calibration technique (C1 and C2) and eight protocols of step calibration technique (C3 to C10) were performed. In C1, weight was added to a stool to match the body mass of each dog. In C2, weight was added to the stool to match a 46.1 kg person. The other eight calibration protocols represented combinations of the following factors: 46.1 kg and 96.1 kg persons, barefoot or wearing sneakers, and stepping onto the platform with one or two feet. RESULTS: The calibration protocols did not affect the temporospatial variables or percentages of body weight (%BW) distribution. Significant differences were found in both PVI (peak vertical force) and VI (vertical impulse) between barefoot versus wearing sneakers, 46.1 kg versus 96.1 kg person, and stepping onto the platform with one foot versus two feet. When comparing C1 with other protocols, significant differences were observed in PVF and VI for both forelimbs and hindlimbs. When comparing C2 with other protocols, significant differences were observed in PVF and VI for both forelimbs and hindlimbs in all protocols. CLINICAL SIGNIFICANCE: The PVF and VI were influenced by the calibration protocol used, but the %BW distribution and temporospatial parameters were not. Using the same calibration protocol for all dogs within the same group eliminated the variability of the kinetic data caused by the calibration.

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.113
GPT teacher head0.349
Teacher spread0.236 · 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 teacher head, not a consensus.

Study designObservational
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

Citations7
Published2014
Admission routes1
Has abstractyes

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