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Reproduction of pre-clinical results has a high failure rate. The fundamentalmethodology including replication ("protocol") for hypothesistesting/validation to a state allowing inference, varies within medical andplant sciences with little justification. Here, five protocols aredistinguished which deal differently with systematic/random errors and varyconsiderably in result veracity. Aim: to compare prevalence of protocols(defined in text). Medical/plant science articles from 2017/2019 were surveyed:713 random articles assessed for eligibility for counts: first (with p-values):1) non-replicated; 2) global; 3) triple-result protocols; second: 4)replication-error protocol; 5) meta-analyses. Inclusion criteria:human/plant/fungal studies with categorical groups. Exclusion criteria: phasedclinical trials, pilot studies, cases, reviews, technology, rare subjects,-omic studies. Abbreviated PICOS question: which protocol was evident for amain result with categorically distinct group difference(s) ? Electronicsources: Journal Citation Reports 2017/2019, Google. Triplication prevalencediffered dramatically between sciences (both years p<10-16; cluster-adjustedchi-squared tests): From 320 studies (80/science/year): in 2017, 53 (66%, 95%confidence interval (C.I.) 56%:77%) and in 2019, 48 (60%, C.I. 49%:71%) plantstudies had triple-result or triplicated global protocols, compared with, inboth years, 4 (5%, C.I. 0.19%:9.8%) medical studies. Plant sciences had ahigher prevalence of protocols more likely to counter generalised systematicerrors (the most likely cause of false positives) and random error thannon-replicated protocols, without suffering from serious flaws found withrandom-Institutes protocols. It is suggested that a triple-result(organised-reproduction) protocol, with Institute consortia, is likely to solvemost problems connected with the replicability crisis.

Repetition and reproduction of preclinical medical studies: taking a  leaf from the plant sciences with consideration of generalised systematic  errors