{"id":"W2316359013","doi":"10.1080/01966324.2007.10737689","title":"Bayesian Analysis of Dyadic Data","year":2007,"lang":"en","type":"article","venue":"American Journal of Mathematical and Management Sciences","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of Connecticut","keywords":"Computer science; Markov chain Monte Carlo; Missing data; Bayesian probability; Variety (cybernetics); Class (philosophy); Variable-order Bayesian network; Inference; Covariate; Data mining; Bayesian inference; Machine learning; Artificial intelligence; Econometrics; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01712363,0.0006468444,0.001458775,0.003552695,0.001040892,0.002796481,0.001760557,0.001347688,0.006681503],"category_scores_gemma":[0.08412847,0.0006596454,0.0009507182,0.003906966,0.001596782,0.003730474,0.002821886,0.002450383,0.0008941333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00130689,"about_ca_system_score_gemma":0.0009614227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004443483,"about_ca_topic_score_gemma":0.004044256,"domain_scores_codex":[0.9857867,0.01053037,0.0003372144,0.001547482,0.001421783,0.0003764227],"domain_scores_gemma":[0.9562414,0.03459507,0.002751714,0.002982347,0.002830909,0.0005985223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002731356,0.0001135613,0.01429722,0.0004073739,0.0004483824,0.0003476243,0.001486752,0.07897249,0.001232165,0.7300207,0.007553779,0.1648468],"study_design_scores_gemma":[0.00002671553,0.00005465138,0.006928482,0.000144664,0.00007677201,0.0002437414,0.00052152,0.3706764,0.0004577781,0.6124315,0.008374986,0.0000626644],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02156015,0.00088146,0.9718451,0.0008211524,0.00004938654,0.00007395,0.0004358678,0.0001540031,0.004178889],"genre_scores_gemma":[0.6585336,0.001986621,0.3310819,0.0003685714,0.0002491846,0.0005966835,0.00153409,0.0001620242,0.005487387],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01712363,"threshold_uncertainty_score":0.09055948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03373646764183357,"score_gpt":0.3319757045146938,"score_spread":0.2982392368728602,"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."}}