The Science
Prokope is evidence-informed. The structure of every system it runs — recovery curves, readiness monitoring, strength-gain feasibility, effort-to-load mapping, running-intensity distribution, protein and energy targets — traces to the peer-reviewed literature below. Some specific magnitudes are practitioner-derived, and we label those where our confidence is lower. We don't claim every number is peer-reviewed — that honesty is the point.
Recovery & freshness
CalibratingTracks recovery muscle by muscle on a non-linear (exponential) curve, so each session trains what's fresh and spares what's still repairing — heavier, higher-RIR, and eccentric work all extend the window.
Engine freshness.ts · Calibrating — Research banked; live-model calibration in progress, held for ship.
Honest note. The curve shape and per-muscle recovery windows come from this literature; a few secondary-mover credits and the running→set-equivalent doses are practitioner estimates, labeled low-confidence in the calibration notes.
Key sources
- Chalchat et al. (2022) — Time course of recovery from exercise-induced muscle damage (141-study meta-analysis) · PMC
- Pareja-Blanco et al. (2017) — Recovery following resistance training to failure vs. not-to-failure · Scand J Med Sci Sports
- Pareja-Blanco et al. (2016) — Velocity loss as a resistance-training stimulus indicator · Scand J Med Sci Sports
- Refalo et al. (2023) — Proximity to failure & acute neuromuscular fatigue · J Strength Cond Res
- Bartolomei et al. (2017) — Recovery after high-intensity vs. high-volume resistance protocols · J Strength Cond Res
- Chen et al. (2019) — Muscle damage & the repeated-bout effect across muscle groups · Eur J Appl Physiol
- Nosaka et al. (2001) — Duration of the protective repeated-bout effect · Med Sci Sports Exerc
- Bontemps et al. (2020) — Downhill (eccentric) running: a narrative review · PMC
- Doma et al. (2019) — Concurrent-training interference & recovery asymmetry · Sports Med 2019;49:669
- Wilson et al. (2012) — Concurrent training interference: a meta-analysis · J Strength Cond Res
- Markov et al. (2022) — Acute effects of aerobic exercise on subsequent strength/power · PMC
Readiness & autoregulation
AppliedA 30-second daily check-in — sleep, energy, soreness, time — sets a readiness score that adjusts the day's volume, load and RIR out loud, rather than silently under- or over-reaching.
Engine readiness.ts · preflight.ts · Applied — Live in the engine today.
Honest note. The instrument (subjective wellness > objective monitoring) and the deload dose-response are directly evidence-based; it shipped calibrated. The exact point deductions remain a tuned mapping on top of that validated structure.
Key sources
- Hooper & Mackinnon (1995) — Monitoring overtraining: recovery & wellness markers · Sports Med
- Saw, Main & Gastin (2016) — Subjective vs. objective monitoring of athlete response (systematic review) · Br J Sports Med
- Laurent et al. (2011) — Perceived Recovery Status (PRS) scale · J Strength Cond Res
- Pareja-Blanco et al. (2017) — Velocity loss during resistance training & adaptation · Scand J Med Sci Sports
- Pelland et al. (2025) — Resistance-training dose-response meta-regression · meta-regression
- Helms et al. (2018) — RPE / RIR autoregulation of training volume · J Strength Cond Res
- Buchheit (2014) — Heart-rate measures for monitoring training status (review) · Front Physiol
- Bell et al. (2025) — A practical approach to deloading (evidence review) · Sheffield Hallam (review, secondary)secondary
Strength-gain feasibility
CalibratingWhen you set a target lift and a date, it charts an honest trajectory from evidence-based weekly gain rates by training age and lift — easing off when you're ahead, adding work when you're behind, and refusing to promise a number that isn't reachable in the time.
Engine goal-program.ts · pacing.ts · Calibrating — Research banked; live-model calibration in progress, held for ship.
Honest note. The gain bands and the %/month × current-e1RM scaling come from these datasets; the overhead-press band and a few derived-lift ratios are extrapolated and flagged lower-confidence.
Key sources
- Latella et al. (2020) — 15-year longitudinal powerlifting progression · PMC
- Latella et al. (2022) — Per-lift rates of strength adaptation · J Strength Cond Res
- Steele & Latella et al. (2023) — Modeling the growth of strength adaptation · Sports Med
- Steele et al. (2022) — Minimal-dose resistance training: long-term strength · J Strength Cond Res
- Ahtiainen et al. (2016) — Heterogeneity of strength response (n=287) · PMC
- Hubal et al. (2005) — Inter-individual variability in strength/size gains · Med Sci Sports Exerc
- Jung et al. (2023) — Lower- vs. upper-body weekly strength gains · PMC
- Brown et al. (2017) — Weekly time-course of neuromuscular adaptation · PMC
- ACSM (2009) — Position Stand: progression models in resistance training · Med Sci Sports Exerc (secondary)secondary
Load & effort (RIR)
CalibratingMaps your target reps and reps-in-reserve to a working weight, and estimates your one-rep max from the sets you actually log — lift-specific, not a single generic formula.
Engine e1rm.ts · Calibrating — Research banked; live-model calibration in progress, held for ship.
Honest note. The max-reps-at-%1RM relationship and 1RM-prediction accuracy are peer-reviewed. The base reps×RIR→%1RM lookup derives from the RTS/Tuchscherer coaching chart, which is practitioner-validated, not peer-reviewed — we disclose that openly and the primary literature calibrates its shape.
Key sources
- Nuzzo, Pinto, Nosaka & Steele (2024) — Maximal reps at a given %1RM: meta-regression · PMC
- Shimano et al. (Kraemer) (2006) — Reps to failure at %1RM in free-weight lifts · J Strength Cond Res 2006;20:819
- Arazi & Asadi (2011) — %1RM–reps relationship: trained vs. untrained · J Hum Kinet
- LeSuer et al. (1997) — Accuracy of 1RM prediction (bench, squat, deadlift) · J Strength Cond Res
- NSCA (2016) — Essentials of Strength Training & Conditioning, 4th ed. (reps↔%1RM) · Human Kinetics (textbook, secondary)secondary
Running
BetaPrescribes easy / threshold / interval paces and paces a run plan toward a goal distance and date, using a mostly-easy intensity distribution and injury-aware progression limits.
Engine pacing.ts · Beta — In active development.
Honest note. The intensity-distribution and injury-progression evidence is strong; the specific pace-zone boundaries follow Daniels' system (a textbook, cited directly) and are still being calibrated against logged data.
Key sources
- Seiler & Kjerland (2006) — Training-intensity distribution in endurance athletes · Scand J Med Sci Sports
- Stöggl & Sperlich (2015) — Polarized training yields greater endurance gains · PMC
- Muñoz et al. (2014) — Polarized vs. threshold training in runners · Int J Sports Physiol Perform
- Rosenblat et al. (2019) — Polarized vs. threshold: a meta-analysis · J Strength Cond Res
- Buist et al. (2008) — GRONORUN: graded running program & injury (RCT) · Am J Sports Med
- Heiderscheit et al. (2011) — Step-rate manipulation & joint loading in running · Med Sci Sports Exerc
- Riegel (1981) — Athletic records & endurance-time prediction · Am Sci
- Daniels (2013) — Daniels' Running Formula (VDOT, E/M/T/I/R zones) · Human Kinetics (textbook, secondary)secondary
Nutrition
CalibratingSets evidence-based protein, calorie and macro targets from your bodyweight, goal and a safe rate of change — enough protein to build or protect muscle, an energy target sized to the trajectory, not a fixed guess.
Engine nutrition.ts · Calibrating — Research banked; live-model calibration in progress, held for ship.
Honest note. Protein plateaus, deficit protein needs and rate-of-gain targets are directly evidence-based; the compliance→expected-progress multiplier is a modeled layer on top.
Key sources
- Morton et al. (2018) — Protein supplementation & resistance training (49-RCT meta-analysis; ~1.6 g/kg plateau) · Br J Sports Med
- Tagawa et al. (2020) — Dose-response of protein on lean mass (105 RCTs) · Nutr Rev
- Helms et al. (2014) — Protein for lean athletes in a deficit (2.3–3.1 g/kg FFM) · Int J Sport Nutr Exerc Metab
- Longland et al. (2016) — High-protein deficit: simultaneous fat loss & lean gain (RCT) · Am J Clin Nutr
- Garthe et al. (2011) — Slow vs. fast weight gain & body composition · Int J Sport Nutr Exerc Metab
- Murphy & Koehler (2021) — Energy deficiency impairs lean-mass gains (meta-analysis) · Scand J Med Sci Sports
- Jäger et al. (ISSN) (2017) — ISSN Position Stand: protein & exercise (1.4–2.0 g/kg) · J Int Soc Sports Nutr (secondary)secondary
Every citation above is primary peer-reviewed literature or a credible secondary source (textbook, position stand, or established training system). Weak or anecdotal sources are deliberately excluded. The full provenance grading lives in the repository's evidence audit. Links open PubMed, PMC, or the publisher via DOI.