MétaCan
Menu
Back to cohort
Record W3169970722 · doi:10.36950/ciss_2019.001

Response to select comments on the proposed paradigm shifts in running

2021· article· en· W3169970722 on OpenAlexaff
Benno M. Nigg, M. Mohr, Sandro Nigg

Bibliographic record

VenueCurrent Issues in Sport Science (CISS) · 2021
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceField (mathematics)Movement (music)Path (computing)Control (management)Human–computer interactionPsychologyPhysical medicine and rehabilitationArtificial intelligenceMedicineAestheticsMathematics

Abstract

fetched live from OpenAlex

Background: Six experts in the field of running-related research have critically addressed a proposal to abandon the paradigms of ‘impact force’ and ‘pronation control’ when investigating running shoes, running injury, and running performance. Further, these experts have commented on the suggestion of the new paradigms of ‘muscle tuning’ and the ‘preferred movement path’ that can be used to investigate questions related to running injuries and performance as well running shoe design and comfort. This publication synthesizes and addresses the main criticisms of the experts and describes future directions to further develop the ‘muscle tuning and ‘preferred movement’ paradigms.

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)0.008
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.036
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.070
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0230.022
Insufficient payload (model declined to judge)0.0360.024

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 head0.036
GPT teacher head0.314
Teacher spread0.277 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Issues in Sport Science (CISS)Same topicLower Extremity Biomechanics and PathologiesFrench-language works237,207