{"id":"W4293769781","doi":"10.1111/soc4.13034","title":"Hacking age","year":2022,"lang":"en","type":"article","venue":"Sociology Compass","topic":"Neuroethics, Human Enhancement, Biomedical Innovations","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University; University of Calgary","funders":"","keywords":"Technoscience; Ambivalence; Sociology; Human enhancement; Natural (archaeology); Transhumanism; Argument (complex analysis); Value (mathematics); Meaning (existential); Epistemology; Frame (networking); Hacker; Environmental ethics; Social science; Social psychology; Psychology; Computer science; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003581366,0.00009767064,0.0001534356,0.0001012206,0.0009686529,0.000014179,0.0004997305,0.00005070394,0.001971918],"category_scores_gemma":[0.0004639813,0.0001064383,0.0000511518,0.0002736591,0.001148536,0.00004550396,0.0004611778,0.0008717661,0.0001646119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009964367,"about_ca_system_score_gemma":0.00005185372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004749613,"about_ca_topic_score_gemma":0.000001530281,"domain_scores_codex":[0.9982718,0.0005132849,0.0002339318,0.0003817636,0.0002701568,0.000329125],"domain_scores_gemma":[0.9989457,0.0006089479,0.0001146311,0.0002655043,0.00001942719,0.00004575949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001120341,0.0001732,0.0004198455,0.000007610957,0.000008702388,0.0001685017,0.002344676,0.00006179071,0.5480497,0.4175007,0.03078531,0.0004687343],"study_design_scores_gemma":[0.001429264,0.0004950099,0.005519606,0.000006974588,0.00001949017,0.00008192638,0.001156369,0.000778698,0.06303033,0.3926753,0.5341684,0.0006386169],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9618967,0.00002722803,0.001783899,0.01672192,0.002610356,0.000255005,0.00004041532,0.0003391374,0.0163254],"genre_scores_gemma":[0.9787737,0.000003330758,0.00010894,0.01954565,0.0001139578,0.00009456363,0.00001165566,0.00001456678,0.00133367],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.503383,"threshold_uncertainty_score":0.9989404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1332205026704189,"score_gpt":0.3552795077826699,"score_spread":0.222059005112251,"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."}}