{"id":"W2727520109","doi":"10.1093/geroni/igx004.4493","title":"AGING AND TECHNOLOGY—TURNING RESEARCH INTO REAL-WORLD IMPACT","year":2017,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Innovative Approaches in Technology and Social Development","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Independence (probability theory); Key (lock); Investment (military); Private sector; Business; Marketing; Public relations; Economic growth; Political science; Economics; Computer science; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003713761,0.0001482521,0.0001916463,0.003930701,0.001603686,0.0004985615,0.000466896,0.0001535078,0.00002382969],"category_scores_gemma":[0.001236422,0.0001482055,0.00001303726,0.004536703,0.000524455,0.001180604,0.0008274777,0.0007955347,0.0000274339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001927878,"about_ca_system_score_gemma":0.00005149349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001010136,"about_ca_topic_score_gemma":0.0002530732,"domain_scores_codex":[0.9985721,0.00001583108,0.0004314067,0.00033797,0.0002378644,0.000404844],"domain_scores_gemma":[0.99855,0.00004788894,0.0003715712,0.0003697764,0.0006568544,0.00000392649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003332372,0.00001076208,0.5260571,0.00003485339,0.00001006834,0.000008657874,0.0002191794,0.000001503699,0.001081374,0.4469053,0.0002404026,0.02542743],"study_design_scores_gemma":[0.0005265576,0.000005341357,0.5994565,0.0002864159,0.000003764691,0.000001457544,0.001638469,0.0006899704,0.001527209,0.3861884,0.009370294,0.0003056044],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9494078,0.00002833487,0.0002636576,0.008950679,0.0002085046,0.000208016,1.956989e-7,0.0001784852,0.04075436],"genre_scores_gemma":[0.9975289,0.00001088452,0.001486585,0.000271346,0.0002944215,0.00005259181,0.00001036355,0.00002084207,0.0003241208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07339936,"threshold_uncertainty_score":0.9996961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0697138022247327,"score_gpt":0.3825383399056794,"score_spread":0.3128245376809466,"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."}}