{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001421282,0.0001995778,0.0002996775,0.0001895341,0.00005076781,0.0001313909,0.0006025677,0.0007078887,0.000002647866],"category_scores_gemma":[0.002271794,0.0002189457,0.00008645697,0.001015783,0.00001225518,0.000003738819,0.002009628,0.0002495395,0.000001919663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000981035,"about_ca_system_score_gemma":0.0002653899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004324199,"about_ca_topic_score_gemma":0.0001041375,"domain_scores_codex":[0.9984568,0.00004586062,0.0004602977,0.000508917,0.000154052,0.0003740833],"domain_scores_gemma":[0.998223,0.0001754917,0.0004234787,0.0009075584,0.0002149228,0.0000555124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008465149,0.0005029574,0.1377452,0.002488285,0.0009596422,0.00001319618,0.0001539559,0.01624311,0.009858709,0.00008689708,0.19179,0.6400733],"study_design_scores_gemma":[0.003551642,0.0005036347,0.06190157,0.001206944,0.0004085872,0.00001322408,0.0001911858,0.2684642,0.001181729,0.001557121,0.6580638,0.002956263],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3731494,0.1536295,0.4375036,0.001137051,0.01612439,0.006769113,0.005153352,0.0001452147,0.006388415],"genre_scores_gemma":[0.6125968,0.003657497,0.3363514,0.0009872519,0.005114632,0.0001984499,0.03996386,0.0001319015,0.000998238],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6371171,"threshold_uncertainty_score":0.8928345,"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."}}