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Record W3047586429 · doi:10.3389/fvets.2020.00459

Quantifying the Forces Applied During Manually and Mechanically Assisted Calvings in Beef Cattle

2020· article· en· W3047586429 on OpenAlexafffund
Jennifer M. Pearson, Charmaine Thomsen, Ann Kusler, Edmund A. Pajor, Akshay Gurdita, Mark Ungrin, M. Claire Windeyer

Bibliographic record

VenueFrontiers in Veterinary Science · 2020
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of WaterlooUniversity of Calgary
FundersFaculty of Veterinary Medicine, University of CalgaryAlberta Agriculture and ForestryUniversity of Calgary
KeywordsIce calvingForce transducerAnimal scienceBeef cattleMathematicsMedicineBiologyPhysicsPregnancy

Abstract

fetched live from OpenAlex

Dystocia is a leading cause of calf mortality, yet there is little available information quantifying the duration and forces applied to assisted deliveries. Objectives of this study were to: (1) develop a method to measure the magnitude and duration of various forces applied to a calf during calving assistance, and (2) quantify the forces applied to beef calves during manual or mechanical calving assistance. Twenty-five primiparous dams requiring calving assistance were enrolled. Calvings were assisted by manual (1 or 2 people pulling) or mechanical (calf extractor) delivery. A set of modified obstetric chains with integrated force measuring devices (Calving Assistance Force Logger; CAF-Log) were applied to the calf for delivery. The CAF-Log system was calibrated using known masses ranging from 25 to 200 kg in increasing increments of 25 kg. Duration of the assisted delivery and force parameters (peak force applied to one leg, peak force applied to both legs, cumulative force, and maximum jerk force) were described and assessed for their associations with method of delivery and ranch. Median duration was 112.6 s (IQR: 88.4-149.7) for manual and 312.6 s (IQR: 221.6-462.3) for mechanical deliveries. Mean peak force applied to one leg was 56.9 kg (SD: 22.9) for manual and 126.8 kg (SD: 48.2) for mechanical deliveries. Mean peak force applied to both legs was 95.4 kg (SD: 34.1) for manual and 188.6 kg (SD: 83.9) for mechanical deliveries. Median cumulative force was 178.3 kg min (IQR: 21.1-38.8) for manual and 380.6 kg min (IQR: 252.1-581.3) for mechanical deliveries. The maximum jerk force for manual deliveries was 36.6 kg/s (IQR: 21.1-38.8) and 77.2 kg/s (IQR: 60.9-97.1) for mechanical deliveries. An interaction occurred between ranch and method of delivery for peak force applied to one leg, peak force applied to both legs, and cumulative force. The CAF-Log system demonstrated that significantly greater forces were applied to mechanically delivered calves compared to manually delivered calves and could be used in future studies to investigate forces applied to a calf during calving assistance and their impacts on cow and calf well-being.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.083
GPT teacher head0.330
Teacher spread0.247 · 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 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

Citations3
Published2020
Admission routes2
Has abstractyes

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