{"id":"W2975521764","doi":"10.1111/biom.13464","title":"Testing for association in multiview network data","year":2021,"lang":"en","type":"preprint","venue":"Biometrics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Institute of General Medical Sciences; Simons Foundation; National Institutes of Health; National Science Foundation","keywords":"Stochastic block model; Computer science; Set (abstract data type); Association (psychology); Node (physics); Null (SQL); Block (permutation group theory); Latent variable; Null model; Data mining; Covariate; Null hypothesis; Data set; Theoretical computer science; Machine learning; Artificial intelligence; Mathematics; Econometrics; Cluster analysis; Psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.03493219,0.0009946731,0.002591127,0.004301724,0.001125979,0.002672435,0.003987632,0.003339784,0.003258733],"category_scores_gemma":[0.1273958,0.0006893947,0.002192914,0.004272066,0.003886671,0.005275808,0.003462987,0.003793641,0.0005500569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001058237,"about_ca_system_score_gemma":0.001206404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001571708,"about_ca_topic_score_gemma":0.0009928826,"domain_scores_codex":[0.960546,0.02160522,0.001698218,0.01093778,0.003844798,0.001368078],"domain_scores_gemma":[0.7755041,0.1873253,0.0162763,0.01612411,0.002767469,0.002002654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003819551,0.0009012427,0.5758075,0.0007278161,0.00472403,0.001870498,0.00134923,0.1406353,0.007307055,0.09472311,0.004188964,0.1639458],"study_design_scores_gemma":[0.0002104761,0.0005614955,0.04213127,0.00008354663,0.000292452,0.0009160855,0.0005330856,0.7769377,0.002429632,0.173604,0.002221698,0.00007852477],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2893594,0.000759184,0.7034761,0.001869547,0.000159641,0.0001805023,0.00240666,0.0005439184,0.001245045],"genre_scores_gemma":[0.9261507,0.0001997425,0.06935591,0.0003441897,0.0002533067,0.0002976269,0.002847323,0.00006197917,0.0004892624],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03493219,"threshold_uncertainty_score":0.1847413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08131336680406438,"score_gpt":0.3135904984382851,"score_spread":0.2322771316342207,"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."}}