MétaCan
Menu
Back to cohort
Record W4256719001 · doi:10.1249/mss.0000000000000677

Response

2015· letter· en· W4256719001 on OpenAlexaffabout
Daniel A. Keir, Federico Y. Fontana, Taylor C. Robertson, Juan M. Murias, Donald H. Paterson, John M. Kowalchuk, Silvia Pogliaghi

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2015
Typeletter
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of CalgaryWestern University
Fundersnot available
KeywordsRespiratory compensationCorrelationMedicineInternal medicineStatisticsMathematicsPsychologyPhysical therapy

Abstract

fetched live from OpenAlex

Dear Editor-in-Chief: The purpose of our recent study (6) was to establish, in a single group of subjects, whether various indices identifying boundaries of sustainable performance shared common characteristics (e.g., pulmonary O2 uptake (V˙O2p)), this being done before attempting to address a mechanistic basis for these indices. Indeed, we showed with a high level of accuracy and precision that the V˙O2p associated with each of critical power (CP), maximal lactate steady state, respiratory compensation point (RCP), and the near-infrared spectroscopy-derived muscle deoxygenation breakpoint were not different (6). Given that in our carefully controlled study, each of the examined “thresholds” occurred at similar V˙O2p values, we believed that this observation could not be ignored and that speculation regarding a common underlying physiological mechanism among indices was warranted. However, Craig et al. (5) strongly oppose this possibility on the basis of their findings, reporting i) an absence of correlation between parameters (specifically RCP and CP) (4) and ii) the existence of a high degree of intrasubject variability among selected parameters (3). First, we question the use of correlational analyses to test correspondence between parameters, where Bland–Altman analysis is considered more appropriate (1). Second, the lack of correlation between V˙O2p associated with CP and RCP in the study of Broxterman et al. (4) may be partly attributable to measurement variability associated with CP, as the variability of V˙O2p at CP seems to be twice that of RCP. In our study, variability was narrower and consistent among all parameters and, as a consequence, minimized the likelihood of a type II error. Therefore, contrary to Craig et al. (5), “absence of evidence” can be considered “evidence of absence,” and thus, the lack of difference among parameters in our study may be appropriately interpreted as equivalence. Regarding the “disservice to the readership by ignoring recent work,” we were unaware of the article by Boone et al. (2) that appeared online a few days before our original submission and was regretfully missed during revision. However, we cannot apologize for lacking the clairvoyance to anticipate the publication of the study of Broxterman et al. (4), which became available online only 4 d before final acceptance of our article. Finally, by no means do we proclaim that our article is the “final word” on the association among these indices, nor do we believe that the issue related to the equivalence between these paradigms is “settled.” That an abundance of methods and indices (each with their own nomenclature) exist to define the intensity beyond which physiological homeostasis can no longer be maintained limits the comparability of data and the availability of a common reference point for subject evaluation, training design, and exercise prescription. In contrast to the opinion of Craig et al. (5), we believe that our study does provide meaningful contribution to this body of literature and does so in a nondictatorial manner. Future work should strive to examine and include the observable “threshold-like” physiological phenomena associated with high intensities of exercise to uncover their mechanistic bases—only then can equivalence or coincidence of their manifestation be concluded. Daniel A. Keir Canadian Centre for Activity and Aging School of Kinesiology University of Western Ontario London, Ontario, CANADA Department of Neurological and Movement Sciences University of Verona Verona, ITALY Federico Y. Fontana Department of Neurological and Movement Sciences University of Verona Verona, ITALY Taylor C. Robertson Canadian Centre for Activity and Aging School of Kinesiology University of Western Ontario London, Ontario, CANADA Juan M. Murias Faculty of Kinesiology University of Calgary Calgary, Alberta, CANADA Donald H. Paterson John M. Kowalchuk Canadian Centre for Activity and Aging School of Kinesiology Department of Physiology and Pharmacology University of Western Ontario London, Ontario, CANADA Silvia Pogliaghi Department of Neurological and Movement Sciences University of Verona Verona, ITALY

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)0.002
metaresearch head score (Gemma)0.024
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: none
Teacher disagreement score0.307
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.3070.178

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 head0.023
GPT teacher head0.294
Teacher spread0.271 · 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

Citations5
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueMedicine & Science in Sports & ExerciseSame topicCardiovascular and exercise physiologyFrench-language works237,207