{"id":"W2801710656","doi":"10.1136/bjsports-2018-099427","title":"Picking the right tools for the job: opening up the statistical toolkit to build a compelling case in sport and exercise medicine research","year":2018,"lang":"en","type":"editorial","venue":"British Journal of Sports Medicine","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Blinding; Blueprint; Sports science; Sports medicine; Process (computing); Analogy; Set (abstract data type); Computer science; Sample (material); Reliability (semiconductor); Psychology; Sample size determination; Applied psychology; Data science; Medicine; Power (physics); Physical therapy; Statistics; Engineering; Mathematics; Pathology; Epistemology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1306403,0.00334465,0.004753,0.009079017,0.004858266,0.01662113,0.008037977,0.0219742,0.005655048],"category_scores_gemma":[0.4566165,0.001853002,0.004143958,0.004031186,0.01407785,0.01599034,0.006277861,0.04481591,0.004498817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003176947,"about_ca_system_score_gemma":0.008853683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001209347,"about_ca_topic_score_gemma":0.002819812,"domain_scores_codex":[0.8761914,0.07460738,0.01711718,0.00301067,0.02792252,0.001150791],"domain_scores_gemma":[0.3292719,0.6109611,0.009306121,0.008468917,0.03646617,0.005525777],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007747895,0.00002221595,0.00009715341,0.002235462,0.0001354391,0.0003280216,0.0007288932,0.0002509535,0.0001337676,0.01430902,0.9463644,0.03531718],"study_design_scores_gemma":[0.0001602047,0.00007581619,0.0002477156,0.006741673,0.0001958282,0.0006173849,0.0004333346,0.001460548,0.0001584506,0.07965972,0.9101069,0.0001424933],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0001052273,0.03416621,0.01592154,0.2838701,0.6638945,0.0001383507,0.0001082486,0.0003871444,0.001408696],"genre_scores_gemma":[0.00235396,0.01901677,0.02570618,0.1217063,0.826753,0.0004739131,0.00007418219,0.0005515921,0.003364235],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.8693597,"threshold_uncertainty_score":0.6909002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4874820110622156,"score_gpt":0.5371273914398379,"score_spread":0.04964538037762228,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}