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Record W2520108362 · doi:10.1515/aoas-2016-0051

Iron Metabolism Modification During Repeated Show Jumping Event in Equine Athletes

2016· article· en· W2520108362 on OpenAlexfundno aff
Giuseppe Piccione, Maria Antonietta Rizzo, Francesca Arfuso, Daniele Bruschetta, Elisabetta Giudice, Anna Assenza

Bibliographic record

VenueAnnals of Animal Science · 2016
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les TechnologiesNational Science Foundation
KeywordsJumpingHorseHematocritRepeated measures designAnalysis of varianceSerum ironHemoglobinAthletesFerritinMedicineIron statusStatistical significancePhysical therapyAnimal sciencePhysiologyInternal medicineIron deficiencyAnemiaBiologyMathematics

Abstract

fetched live from OpenAlex

Abstract In athletic horse the evaluation of iron status is of great importance to improve physical performance and health status of animal. The aim of this study was to evaluate the changes of iron indices following show jumping. Ten regularly trained Italian Saddlebred horses aged 7-8 years (mean body weight 467±12 kg) were subjected to three days jumping competition. Blood samples were collected at 5 time points: T0 (the day before competitions), T1 (immediately after exercise at day 1), T2 (immediately after exercise at day 2), T3 (immediately after exercise at day 3) and during the recovery period T4 (24 h after day 3). On each blood sample the values of red blood cell (RBC), hemoglobin concentration (Hb), hematocrit (Hct), serum iron, ferritin, transferrin, total iron-binding capacity (TIBC) and unsaturated iron-binding capacity (UIBC) were assessed. One-way repeated measure analysis of variance (ANOVA) showed a statistical significant effect of exercise (P<0.05) on all studied parameters. The application of Bonferroni’s post-hoc comparison showed a statistical significant increase in all studied parameters after exercise. These results provide new information about the changes in iron profile of jumper horse following exercise allowing for better evaluation of the health status and physical performance of this athlete horse.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.242
GPT teacher head0.457
Teacher spread0.214 · 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.

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

Citations4
Published2016
Admission routes1
Has abstractyes

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