{"id":"W4396600666","doi":"10.1093/geront/gnae039","title":"Addressing the Black Box of AI—A Model and Research Agenda on the Co-constitution of Aging and Artificial Intelligence","year":2024,"lang":"en","type":"article","venue":"The Gerontologist","topic":"Aging and Gerontology Research","field":"Psychology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University; Brock University","funders":"Canadian Institutes of Health Research; Karl Landsteiner Privatuniversität für Gesundheitswissenschaften; Social Sciences and Humanities Research Council of Canada; Vienna Science and Technology Fund","keywords":"Constitution; Black box; Field (mathematics); Artificial intelligence; Sociology; Epistemology; Computer science; Psychology; Cognitive science; Data science; Political science; Law; Philosophy","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.003946234,0.0001171902,0.0001860711,0.00009528401,0.0004636432,0.00007957178,0.0003997815,0.0001086417,0.00007342206],"category_scores_gemma":[0.0002698583,0.00005514223,0.00004388428,0.0002016569,0.006938089,0.00004852773,0.0001354661,0.0008619654,0.00003122239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002534794,"about_ca_system_score_gemma":0.00009735397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007478175,"about_ca_topic_score_gemma":0.000322424,"domain_scores_codex":[0.9979115,0.0008374761,0.0002844463,0.0003092132,0.0002862848,0.0003710486],"domain_scores_gemma":[0.9972339,0.002076609,0.00005884299,0.0005099379,0.00008883853,0.00003181989],"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":[0.000274651,0.0000679908,0.0006547872,0.000103477,0.0001337249,0.00002491878,0.02990233,0.0002924785,0.0008289751,0.8996119,0.008021445,0.06008326],"study_design_scores_gemma":[0.0007359367,0.001767833,0.01559887,0.001801232,0.0003814826,0.0005308177,0.1772615,0.2661463,0.03441107,0.4951183,0.005196969,0.001049736],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9031343,0.008383496,0.008977406,0.03277504,0.0002543778,0.0005572252,0.00002947671,0.00005092943,0.04583773],"genre_scores_gemma":[0.9988518,0.00006433731,0.00003443914,0.0001529343,0.00006369538,0.00002595977,0.000001580858,0.000007933068,0.0007973521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4044937,"threshold_uncertainty_score":0.9957644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5329663394895351,"score_gpt":0.5323329774988196,"score_spread":0.0006333619907155086,"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."}}