{"id":"W2083198307","doi":"10.1177/0263276411427409","title":"Investing in Life, Investing in Difference: Nations, Populations and Genomes","year":2012,"lang":"en","type":"article","venue":"Theory Culture & Society","topic":"Race, Genetics, and Society","field":"Biochemistry, Genetics and Molecular Biology","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Variation (astronomy); Sociology; Meaning (existential); Population; Vitality; Nexus (standard); Social science; Relevance (law); Politics; Epistemology; Environmental ethics; Biology; Political science; Law; Demography; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000664292,0.0001533453,0.0001451527,0.00002046133,0.0002017572,0.00002706001,0.0001068031,0.0002391992,0.000005355865],"category_scores_gemma":[0.0003662147,0.0001400695,0.0000800726,0.0001842451,0.0001716749,0.00001129143,0.0001055543,0.0002061126,0.000001472054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003217771,"about_ca_system_score_gemma":0.00005331987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002504025,"about_ca_topic_score_gemma":0.000151632,"domain_scores_codex":[0.9989791,0.0001507164,0.0002279455,0.0002409979,0.00009251735,0.0003087217],"domain_scores_gemma":[0.999555,0.00003252324,0.00007652724,0.00017367,0.00004058212,0.0001217321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001183676,0.0001411479,0.787815,0.00008076539,0.00005210936,4.01154e-7,0.05873336,0.0001880478,0.1275579,0.02246028,0.00157249,0.001386594],"study_design_scores_gemma":[0.001678454,0.0000960731,0.9027415,0.0001089191,0.00005985971,0.00001595184,0.0557118,0.0004353059,0.005317321,0.02395138,0.008916893,0.000966555],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9862965,0.01157282,0.0002198612,0.0001158986,0.00009237065,0.0001586524,0.000008379946,0.00001558709,0.001519922],"genre_scores_gemma":[0.9914671,0.001230654,0.005264718,0.0008790166,0.0003285532,0.00002223081,0.00008364578,0.00001700472,0.0007070529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1222406,"threshold_uncertainty_score":0.5711867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02299857761996584,"score_gpt":0.2719573531863793,"score_spread":0.2489587755664134,"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."}}