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Chris Farhood 85b6be4e36 fix(vo2max): rebalance rep-length conflict, correct overstatements

Review of the VO2 conflict section against primary sources (verified via
PubMed + search):

- Rønnestad & Hansen 2016 (PMID 23942167) confirmed: 13 cyclists, 30s vs
  50%/80% Tmax at 2:1 work:rest, measured time >=90% VO2peak, 30s won. Table
  row corrected to reflect the actual comparison.
- Yang 2025 optimum ~140s is a MEDIUM rep (~2.3 min), between the poles.
  Section reframed from binary short-vs-long to an inverted-U with a
  modality/protocol-dependent peak. 'Weighted toward running' softened to
  match what the abstract actually supports.
- Removed the overstatement 'best-controlled evidence favors short 30/15
  intervals'. Added two caveats: (1) cycling short-interval superiority is
  largely one research group; (2) effort-matched work (total-work-matched)
  reportedly nulls the advantage (Seiler group; unpublished/secondary,
  flagged low-tier, not cited as fact).
- Practical menu now defaults to medium (~2-4 min, near the pooled optimum)
  rather than short; short/long presented as goal-dependent options.
- citations.md: added single-group caveat on Ronnestad body of work and an
  explicit NOT-VERIFIABLE entry for the effort-matched replication.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TqrhBhC3GEcKyaw8RTk8G6

2026-07-20 19:05:12 -04:00

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Raw Blame History

Master citation list

The single source of truth for every quantitative claim in this skill. Each entry: full citation, PMID/DOI, and a confidence flag from verification against PubMed / DOI resolvers.

Confidence key:

✅ Confirmed — PMID and/or DOI verified; title, authors, journal internally consistent.
⚠️ Confirmed metadata, claim = commonly-cited/approximate — the paper exists as cited, but the exact number attributed to it is widely-repeated rather than verified word-for-word in the source.
❌ Not found — could not be confirmed; do not cite as fact.

Verified as of 2026-07-20.

Durability / fatigue resistance

✅ Muriel et al. 2022 — fatigued-state power differentiates riders; fresh power does not. Muriel X, Mateo-March M, Valenzuela PL, Zabala M, Lucia A, Pallarés JG, Barranco-Gil D. Durability and repeatability of professional cyclists during a Grand Tour. Eur J Sport Sci. 2022;22(12): 1797–1804. PMID 34586952 · DOI 10.1080/17461391.2021.1987528.

✅ Spragg, Leo & Swart 2023 (training characteristics) — durability tracks accumulated volume/load; fatigued profile varies more than fresh across a season. This is the primary "load dependency" cite. Spragg J, Leo P, Swart J. The relationship between training characteristics and durability in professional cyclists across a competitive season. Eur J Sport Sci. 2023;23(4): 489–498. PMID 35239466 · DOI 10.1080/17461391.2022.2049886.

The crisp "reduced load maintains fresh power; sustained load maintains durability" phrasing is Spragg's applied interpretation of this data — attribute as commentary, not a quoted result.

✅ Spragg, Leo & Swart 2023 (physiological characteristics) — physiological correlates of durability (higher VO2max, gross efficiency, fat oxidation). Spragg J, Leo P, Swart J. The Relationship between Physiological Characteristics and Durability in Male Professional Cyclists. Med Sci Sports Exerc. 2023;55(1):133–140. PMID 35977108 · DOI 10.1249/MSS.0000000000003024.

✅ Maunder et al. 2021 — canonical definition of durability as a distinct profiling quality. Maunder E, Seiler S, Mildenhall MJ, Kilding AE, Plews DJ. The Importance of 'Durability' in the Physiological Profiling of Endurance Athletes. Sports Med. 2021;51(8):1619–1628. PMID 33886100 · DOI 10.1007/s40279-021-01459-0.

MTB / XCO demands

✅ Hays et al. 2018 — XCO demand profile (~25% time above MAP; hard start); HR/power/VO2 dissociation (VO2 high on descents, %VO2max uncorrelated with %HRmax/%MAP). Hays A, Devys S, Bertin D, Marquet LA, Brisswalter J. Understanding the Physiological Requirements of the Mountain Bike Cross-Country Olympic Race Format. Front Physiol. 2018;9:1062. PMID 30158873 · DOI 10.3389/fphys.2018.01062.

✅ Prinz et al. 2021 — corroborating hard-number demand data (~30% top zone; 334 efforts ~4.3 s at ~135% MAP). Prinz B, et al. (power-profile / demands of XCO) Int J Sports Physiol Perform. 2021. PMID 33848975 · DOI 10.1123/ijspp.2020-0758.

✅ Protzen et al. 2026 — systematic review: contemporary XCO shifted toward greater anaerobic contribution while maintaining high aerobic demand; ~¼ race time above MAP. Protzen G, Inoue A, Buzzachera CF, Doma K, Devantier-Thomas B, Herrero-Molleda A, García-López J, Boullosa D. The Physiology of Contemporary Olympic Cross-Country Mountain Biking: A Systematic Review. Sports Med Open. 2026;12:16. PMID 41739301 · DOI 10.1186/s40798-026-00976-4.

✅ Impellizzeri et al. 2005 — aerobic predictors of XCO (mass-normalized threshold power/VO2). Frame r ≈ 0.6–0.9 as "across studies"; the elite-cohort raw VO2max did not separate riders. Impellizzeri FM, Marcora SM, Rampinini E, Mognoni P, Sassi A. Correlations between physiological variables and performance in high level cross country off road cyclists. Br J Sports Med. 2005;39(10):747–751. PMID 16183772 · DOI 10.1136/bjsm.2004.017236.

✅ Inoue et al. 2012 — anaerobic power predicts XCO race time (r = −0.79, p = 0.006). Inoue A, Sá Filho AS, Mello FCM, Santos TM. Relationship between anaerobic cycling tests and mountain bike cross-country performance. J Strength Cond Res. 2012;26(6):1589–1593. PMID 21912290 · DOI 10.1519/JSC.0b013e318234eb89.

✅ Sánchez-Jiménez et al. 2025 — fatigue-decline magnitudes: Top-10 ~6–10% vs lower ~15–20%. Sánchez-Jiménez L, Javaloyes A, Peña-González I, Moya-Ramón M, Mateo-March M. Record Power Profile in Elite Olympic Cross-Country Mountain Bike Cyclists: Normative Values and Fatigue Effects. Scand J Med Sci Sports. 2025;35(11):e70170. PMID 41285697 · DOI 10.1111/sms.70170.

✅ Novak et al. 2018 — marathon (4-h) MTB predictors differ from lap XCO. Novak AR, Bennett KJM, Fransen J, Dascombe BJ. Predictors of performance in a 4-h mountain-bike race. J Sports Sci. 2018;36(4):462–468. PMID 28406361 · DOI 10.1080/02640414.2017.1313999.

Strength training (incl. masters)

✅ Llanos-Lagos et al. 2026 (epub 2025) — meta-analysis, 17 studies / 262 cyclists: heavy strength improves efficiency, anaerobic power, TT performance; no VO2max effect. Llanos-Lagos C, Ramírez-Campillo R, Sáez de Villarreal E. Heavy strength training effects on physiological determinants of endurance cyclist performance: a systematic review with meta-analysis. Eur J Appl Physiol. 2026;126(1):193–222. PMID 40632222 · DOI 10.1007/s00421-025-05883-2. (Certainty of evidence noted as low by the authors.)

✅ Cadore et al. 2013 (epub 2012) — strength-first sequencing yields greater strength gains in the elderly (~35% vs ~22%). Cadore EL, Izquierdo M, Pinto SS, et al. Neuromuscular adaptations to concurrent training in the elderly: effects of intrasession exercise sequence. Age (Dordr). 2013;35(3):891–903. PMID 22453934 · DOI 10.1007/s11357-012-9405-y. (This is the "Cadore 2012" sequencing cite.)

✅ Cadore & Izquierdo 2013 — interference manageable/muted in older adults except at high volume/frequency. Cadore EL, Izquierdo M. How to simultaneously optimize muscle strength, power, functional capacity, and cardiovascular gains in the elderly: an update. Age (Dordr). 2013;35(6):2329–2344. PMID 23288690 · DOI 10.1007/s11357-012-9503-x.

⚠️ English & Paddon-Jones 2010 — commonly cited origin of "~8% muscle loss/decade after 40." Exact figure not verified in abstract; treat as commonly-cited/approximate. English KL, Paddon- Jones D. Protecting muscle mass and function in older adults during bed rest. Curr Opin Clin Nutr Metab Care. 2010;13(1):34–39. PMID 19898232 · DOI 10.1097/MCO.0b013e328333aa66.

✅ Volpi, Nazemi & Fujita 2004 — sarcopenia mechanisms; resistance/aerobic training as countermeasure (fiber-type-fastest specifics not verbatim-confirmed). Volpi E, Nazemi R, Fujita S. Muscle tissue changes with aging. Curr Opin Clin Nutr Metab Care. 2004;7(4):405–410. PMID 15192443 · DOI 10.1097/01.mco.0000134362.76653.b2.

✅ Cruz-Jentoft et al. 2019 (EWGSOP2) — consensus: sarcopenia centers on muscle strength; resistance training recommended. Strongest confirmed cite for "loaded resistance is the primary countermeasure." Cruz-Jentoft AJ, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(1):16–31. PMID 30312372 · DOI 10.1093/ageing/afy169.

VO2max intervals

✅ Yang, Wang & Guan 2025 — network meta-analysis, 51 studies / 1,261 athletes: inverted-U dose-response; optimum ~140 s work, work:rest ~0.85. Weighted toward running-based HIIT. Yang Q, Wang J, Guan D. Comparison of different interval training methods on athletes' oxygen uptake: a systematic review with pairwise and network meta-analysis. BMC Sports Sci Med Rehabil. 2025;17(1):156. PMID 40605061 · DOI 10.1186/s13102-025-01191-6.

✅ Fleckenstein, Braunstein & Walter 2025 — running: long (3-min) intervals accumulate more time >90% VO2max than intensified 30-s intervals. Fleckenstein D, Braunstein H, Walter N. Faster intervals, faster recoveries — intensified short VO2max running intervals are inferior to traditional long intervals in terms of time spent above 90% VO2max. Front Sports Act Living. 2025;6:1507957. PMID 39835194 · DOI 10.3389/fspor.2024.1507957.

✅ Rønnestad & Hansen 2016 — cycling, opposite result: 30-s intervals induced more time ≥90% VO2peak than longer intervals. Rønnestad BR, Hansen J. Optimizing Interval Training at Power Output Associated With Peak Oxygen Uptake in Well-Trained Cyclists. J Strength Cond Res. 2016;30(4): 999–1006. PMID 23942167 · DOI 10.1519/JSC.0b013e3182a73e8a. (Often mis-cited as 2013 = epub.)

✅ Rønnestad et al. 2020 — cycling: short (30/15 s) beat effort-matched long (5-min) intervals over 3 weeks (+4.7% 20-min power) in elite cyclists. Rønnestad BR, Hansen J, Nygaard H, Lundby C. Superior performance improvements in elite cyclists following short-interval vs effort-matched long-interval training. Scand J Med Sci Sports. 2020;30(5):849–857. PMID 31977120 · DOI 10.1111/sms.13627.

✅ Almquist et al. 2020 — effort-matched acute systemic/muscular responses favor short intervals. Almquist NW, Nygaard H, Vegge G, Hammarström D, Ellefsen S, Rønnestad BR. Systemic and muscular responses to effort-matched short intervals and long intervals in elite cyclists. Scand J Med Sci Sports. 2020;30(7):1140–1150. PMID 32267032 · DOI 10.1111/sms.13672.

✅ Rønnestad et al. 2021 — microcycle shock-block: short intervals → superior adaptations. Rønnestad BR, Øfsteng SJ, Zambolin F, Raastad T, Hammarström D. Superior Physiological Adaptations After a Microcycle of Short Intervals Versus Long Intervals in Cyclists. Int J Sports Physiol Perform. 2021;16(10):1432–1438. PMID 33735833 · DOI 10.1123/ijspp.2020-0647.

Caveat on the cycling short-interval body of work (Rønnestad 2016/2020/2021 + Almquist 2020): the short-interval superiority comes chiefly from a single research group, and its adaptation claims are challenged by effort-matched work: when total work duration is matched, the advantage reportedly disappears (attributed to a Seiler-group study — unpublished / secondary-source, low evidence tier, not cited as fact). Present short-interval superiority as a lab-consistent but not independently settled finding, not a cycling consensus. See vo2max-intervals.md.

❌ "Effort-matched cycling replication, no difference" (Seiler group) — NOT VERIFIABLE as a primary source. Referenced only via secondary/coaching sources as an unpublished master's thesis (~30 cyclists, VO2max ~64, total-work-matched, no short-vs-long difference). Used only to temper overconfidence in the short-interval side; do not cite as established evidence.

Distribution / periodization philosophy

✅ Seiler 2024 — "long game, not epic workouts"; HIIT is not an acute-maximization problem; polarized training as a context-dependent principle. Peer-reviewed Perspective (open access). Seiler S. It's about the long game, not epic workouts: unpacking HIIT for endurance athletes. Appl Physiol Nutr Metab. 2024;49(11):1585–1599. PMID 39079169 · DOI 10.1139/apnm-2024-0012.

✅ Sun, Yu et al. 2025 — review of training-intensity-distribution models: no single model universally superior; adapt to sport/phase/athlete. (Use for the "distribution is context- dependent" point — it does NOT claim frequency > distribution.) Sun Q, Yu Y, Cui J, Lin S, Wang X, Zhou T. Recent advances in training intensity distribution theory for cyclic endurance sports. Front Physiol. 2025;16:1657892. PMID 41169886 · DOI 10.3389/fphys.2025.1657892.

❌ "Yu et al. 2025" (frequency > distribution) — NOT FOUND. No PubMed paper with Yu as first author making this specific claim could be located. Do not cite. The nearest real paper (Sun/Yu 2025, above) does not support "frequency outweighs distribution." Ground the frequency point in Seiler 2024 instead, and label it a heuristic, not a quantified finding.

Notes on verification method

All ✅ identifiers were read from PubMed record pages and cross-checked against DOI resolvers by independent verification agents on 2026-07-20. Where a claim's number is widely repeated but not verbatim in the source abstract, it is marked ⚠️ and the reference docs say so inline. No identifier in this list was fabricated; the one unlocatable citation is explicitly marked ❌.

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