{"id":"W2793972423","doi":"10.1007/s10823-018-9344-x","title":"Validation of a Social Networks and Support Measurement Tool for Use in International Aging Research: The International Mobility in Aging Study","year":2018,"lang":"en","type":"article","venue":"Journal of Cross-Cultural Gerontology","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University; Université de Montréal","funders":"Institute of Aging; Universidade Federal do Rio Grande do Norte; Universidad de Caldas","keywords":"Psychology; Confirmatory factor analysis; Goodness of fit; Likert scale; Social support; Sample (material); Scale (ratio); Reliability (semiconductor); Social network (sociolinguistics); Developmental psychology; Structural equation modeling; Social psychology; Gerontology; Clinical psychology; Social media; Medicine; Statistics; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008879267,0.00006213468,0.0002011781,0.0001110141,0.0003087,0.000235229,0.0003176593,0.00007105893,0.00005349164],"category_scores_gemma":[0.002094132,0.0000432227,0.00005593751,0.0001120773,0.000599632,0.0007895557,0.0000722608,0.0002531585,2.112737e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004674734,"about_ca_system_score_gemma":0.0003102247,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003025387,"about_ca_topic_score_gemma":0.02784775,"domain_scores_codex":[0.9979362,0.0004044813,0.0006295259,0.0001199543,0.0006297148,0.0002801254],"domain_scores_gemma":[0.9972234,0.0003790987,0.0002873758,0.00005007784,0.00201977,0.00004030229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002587689,0.0001974743,0.9627623,0.00001275532,0.00003361541,0.00000351824,0.02855128,0.00003254363,0.00003262702,0.002316155,0.0004851354,0.005313805],"study_design_scores_gemma":[0.001094852,0.0001410334,0.9675127,0.00003709492,0.000006178811,0.000005575728,0.02255597,0.0001795238,0.00002681234,0.00060411,0.007782058,0.00005411837],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918998,0.00005572523,0.00007819335,0.006205758,0.001041216,0.0003404132,0.000002767436,0.000002317897,0.0003737967],"genre_scores_gemma":[0.9988152,0.00002839432,0.0001088691,0.0002386662,0.0006860516,0.00001523587,0.000001240383,0.000003003542,0.0001033059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02482236,"threshold_uncertainty_score":0.9898915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2941334258412635,"score_gpt":0.5196508338623749,"score_spread":0.2255174080211114,"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."}}