{"id":"W147248661","doi":"10.15760/etd.451","title":"The impact of social networks on mortality, disease incidence, and disease progression","year":2000,"lang":"en","type":"report","venue":"","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social network (sociolinguistics); Disease; Gerontology; Logistic regression; Longitudinal study; Demography; Social support; Medicine; Psychology; Environmental health; Social psychology; Computer science; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001612734,0.0002082164,0.0001608822,0.001276679,0.0004733268,0.0006264044,0.000258817,0.0002561886,0.001721212],"category_scores_gemma":[0.01132479,0.00009990793,0.0002837886,0.0009193048,0.0003110728,0.0008136813,0.0008640568,0.0004550623,0.000136177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000416303,"about_ca_system_score_gemma":0.0003111351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004368867,"about_ca_topic_score_gemma":0.008092536,"domain_scores_codex":[0.9984952,0.0008667818,0.00006843361,0.0001217925,0.0002574857,0.0001903359],"domain_scores_gemma":[0.9921808,0.003402496,0.002575752,0.0002774676,0.0004735655,0.001089943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009523133,0.00006467394,0.9879977,0.00002135126,0.0001236755,0.0000592193,0.0001641999,0.0003374578,0.00009156709,0.0002279078,0.0001071404,0.01070995],"study_design_scores_gemma":[0.000002249945,0.00007548235,0.9984199,0.00001328588,0.0000385278,0.0000803868,0.0001543726,0.0006438452,0.00003719918,0.0002334525,0.0002973156,0.000004079739],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950888,0.001174145,0.0002913928,0.0002727657,0.00001095936,0.0000120843,0.0003237289,0.000005867521,0.002820431],"genre_scores_gemma":[0.9992849,0.0003362099,0.00008194236,0.000008540429,0.00001722001,0.00000702481,0.0001152671,8.912666e-7,0.0001480539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004368867,"threshold_uncertainty_score":0.0086869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05373108553327417,"score_gpt":0.4641301445715282,"score_spread":0.410399059038254,"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."}}