{"id":"W4405092109","doi":"10.3148/cjdpr-2024-019","title":"How Many Participants Are Needed? Strategies for Calculating Sample Size in Nutrition Research","year":2024,"lang":"en","type":"review","venue":"Canadian Journal of Dietetic Practice and Research","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"","keywords":"Sample size determination; Sample (material); Robustness (evolution); Computer science; Estimation; Reliability (semiconductor); A priori and a posteriori; Statistics; Management science; Data science; Power (physics); Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":["metaresearch"],"category_scores_codex":[0.4490918,0.003022762,0.006961785,0.009213352,0.00289206,0.008025615,0.006162686,0.00795179,0.009919147],"category_scores_gemma":[0.7216949,0.003151554,0.006470165,0.009343281,0.006913037,0.01602994,0.007916608,0.01021698,0.003075617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005802934,"about_ca_system_score_gemma":0.01737938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004494723,"about_ca_topic_score_gemma":0.00736827,"domain_scores_codex":[0.3871449,0.4976066,0.06728768,0.009267288,0.03737604,0.00131745],"domain_scores_gemma":[0.4006028,0.5338165,0.02258068,0.01774626,0.02304551,0.002208275],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001957924,0.0002074811,0.004182731,0.0484282,0.002350606,0.0003572499,0.01246797,0.002290945,0.001308387,0.08245732,0.04409523,0.799896],"study_design_scores_gemma":[0.005739997,0.002311437,0.009878755,0.1444857,0.005676073,0.001210084,0.005443927,0.01017617,0.005230817,0.4533436,0.3557366,0.0007667987],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.007125627,0.0816301,0.7131274,0.06951093,0.01332055,0.09349146,0.003738236,0.001296114,0.01675964],"genre_scores_gemma":[0.03215044,0.01265659,0.7669458,0.01329742,0.001073973,0.171798,0.0005738597,0.0002491261,0.001254736],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.5509082,"threshold_uncertainty_score":0.6793679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9409783114672453,"score_gpt":0.6857773407491243,"score_spread":0.255200970718121,"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."}}