{"id":"W4416921232","doi":"10.1080/03610918.2025.2593940","title":"Beyond conventional <i>p</i> -values: addressing statistical challenges in big data","year":2025,"lang":"en","type":"article","venue":"Communications in Statistics - Simulation and Computation","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of Victoria","funders":"National Research Council Canada; Alliance de recherche numérique du Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Michael Smith Health Research BC","keywords":"Big data; Key (lock); Field (mathematics); Data collection; Work (physics)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009098711,0.0001400383,0.0002287078,0.0005453101,0.0001917753,0.0002348549,0.001379256,0.00006828444,0.000004201664],"category_scores_gemma":[0.0005102784,0.0001636456,0.00001215235,0.0007707414,0.0001796407,0.0005719677,0.001274376,0.0002329849,0.000008181634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008566963,"about_ca_system_score_gemma":0.0001575442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004279996,"about_ca_topic_score_gemma":0.0004961168,"domain_scores_codex":[0.9979507,0.0004786025,0.0006537415,0.00048948,0.0002504471,0.0001769815],"domain_scores_gemma":[0.9953952,0.002570149,0.0001638227,0.001651076,0.0001726581,0.00004711513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007066806,0.0001723724,0.002221419,0.00004247697,0.00001671599,0.000002769049,0.0003730639,0.04694753,0.000002899469,0.5113029,0.0004341757,0.4384766],"study_design_scores_gemma":[0.0005736175,0.0000107278,0.03519929,0.00007900441,0.00001378816,9.326386e-7,0.0001149063,0.8081837,6.787439e-7,0.1544794,0.001227697,0.0001162006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002878369,0.001770627,0.994153,0.001331811,0.0001657958,0.0002099563,0.0002328608,0.00005080412,0.001797366],"genre_scores_gemma":[0.6825313,0.0005561197,0.3149457,0.0001623308,0.00001153744,0.00001507904,0.001749591,0.000005881426,0.00002246711],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7612362,"threshold_uncertainty_score":0.6673275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3533042758896263,"score_gpt":0.4748988450326684,"score_spread":0.1215945691430421,"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."}}