{"id":"W4402761393","doi":"10.1177/00236772241247106","title":"Understanding <i>p</i> -values and significance","year":2024,"lang":"en","type":"article","venue":"Laboratory Animals","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Selection (genetic algorithm); Interpretation (philosophy); Computer science; Statistics; Multiple comparisons problem; Selection bias; Econometrics; Data science; Mathematics; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.05458979,0.00018474,0.001262855,0.0002032375,0.0001371411,0.002155926,0.0005081405,0.00005759636,0.004164292],"category_scores_gemma":[0.006217475,0.00009335735,0.0003173341,0.001716343,0.00009148371,0.000326568,0.00006168457,0.0001125618,0.002243933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003786683,"about_ca_system_score_gemma":0.00008013169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.187242e-7,"about_ca_topic_score_gemma":0.000003575017,"domain_scores_codex":[0.9911977,0.003007433,0.002777479,0.0008172785,0.002022316,0.0001777837],"domain_scores_gemma":[0.994891,0.002981719,0.0005615655,0.001141766,0.0002980804,0.0001258213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008391598,0.00001873133,0.01193807,0.0002412798,0.0002847428,0.00008975188,0.001547316,0.00002092679,0.01714765,0.4506245,0.5155511,0.002527573],"study_design_scores_gemma":[0.00009347903,0.00007197673,0.003011762,0.0001462135,0.0002175812,0.0000105361,0.003502717,0.005115044,0.0009574358,0.2156085,0.7708872,0.0003776104],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6717654,0.0930011,0.1189362,0.005558992,0.002219717,0.001745853,0.0003678608,0.0001835036,0.1062214],"genre_scores_gemma":[0.9940646,0.00007033073,0.001121266,0.0003341542,0.0001175357,0.00001335522,6.87645e-7,0.00001180364,0.00426621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3222992,"threshold_uncertainty_score":0.9988799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7807173623407296,"score_gpt":0.5086724211872989,"score_spread":0.2720449411534307,"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."}}