{"id":"W4404906980","doi":"10.1386/public_00226_4","title":"Alexis Kyle Mitchell: The Treasury of Human Inheritance (2024)","year":2024,"lang":"en","type":"article","venue":"Public","topic":"Reproductive Health and Technologies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Treasury; Inheritance (genetic algorithm); Genealogy; History; Biology; Genetics; Archaeology; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009307536,0.0003488363,0.0002004172,0.000588387,0.002188779,0.003252689,0.000648174,0.002993114,0.008034199],"category_scores_gemma":[0.003130233,0.0001634033,0.000154476,0.0006121394,0.003695874,0.002181586,0.001705618,0.003885717,0.002097613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004407683,"about_ca_system_score_gemma":0.003251159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04267767,"about_ca_topic_score_gemma":0.07834341,"domain_scores_codex":[0.9990011,0.0002948894,0.00003919325,0.0001051838,0.0004589916,0.0001007534],"domain_scores_gemma":[0.9993339,0.0002369965,0.00005966486,0.00002860519,0.0001826791,0.0001580941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002232401,0.000009204178,0.0003222081,0.0004659411,0.000006114178,0.0004660347,0.006253454,0.00004876469,0.0002368156,0.05042813,0.8534939,0.08824708],"study_design_scores_gemma":[9.724005e-7,0.000003144283,0.0002745845,0.0003386992,0.000001074225,0.000338916,0.0007061911,0.000005791479,0.00004855814,0.000810201,0.9974686,0.000003255372],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"other","genre_scores_codex":[0.002102977,0.658522,0.0005190119,0.1807786,0.03003464,0.00001902706,0.00005244784,0.00003414764,0.1279372],"genre_scores_gemma":[0.0875524,0.5759872,0.001074198,0.0886118,0.02847413,0.00006008924,0.00009120355,0.0001016277,0.2180474],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04267767,"threshold_uncertainty_score":0.08485854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07266872309101838,"score_gpt":0.3464856146923552,"score_spread":0.2738168916013368,"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."}}