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Record W3157524757 · doi:10.1519/ssc.0000000000000643

A Review of Striking Force in Full-Contact Combat Sport Athletes: Methods of Assessment

2021· review· en· W3157524757 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStrength and conditioning journal · 2021
Typereview
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsCanadian Sport Centre Pacific
Fundersnot available
KeywordsMartial artsAthletesApplied psychologyPsychologyReliability (semiconductor)Track and field athleticsComputer scienceMedicinePhysical therapyHistory

Abstract

fetched live from OpenAlex

ABSTRACT With striking force playing such a critical role in the success of full-contact combat sports such as mixed martial arts, taekwondo, and boxing, coaches and scientists must be able to track this performance metric accurately and reliably. This review will cover practitioner understanding of key kinetic variables used in the assessment of striking important concepts relating to the validity, reliability, and reporting of meaningful performance changes in the assessment process, a critique of the methods used to monitor changes in striking forces, and provide practical recommendations for practitioners in the field. This understanding will help coaches and scientists assess and interpret the effectiveness of training.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.923
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.434
Teacher spread0.384 · 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