{"id":"W7134068206","doi":"10.5281/zenodo.18885506","title":"Transformation of the Lebanon National Genebank through BOLD","year":2025,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Dermatoglyphics and Human Traits","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Transformation (genetics); Government (linguistics); Indigenous; Ethnic group","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006563176,0.0006492941,0.0006025026,0.005652592,0.000886664,0.00204192,0.001095354,0.0004429454,0.09922642],"category_scores_gemma":[0.01034695,0.0005472453,0.0005514611,0.005440454,0.0003474899,0.001456628,0.002513305,0.001334158,0.06905698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001279077,"about_ca_system_score_gemma":0.00323372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009329617,"about_ca_topic_score_gemma":0.006527884,"domain_scores_codex":[0.9985575,0.0003692579,0.000225058,0.0002822929,0.0003980642,0.0001677722],"domain_scores_gemma":[0.9938536,0.001274588,0.0003516914,0.001828547,0.00222231,0.000469462],"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":[0.001082514,0.0001082058,0.002372598,0.0004479597,0.00005745916,0.000375337,0.0008392667,0.0003335386,0.01035667,0.01076888,0.8788314,0.09442601],"study_design_scores_gemma":[0.000134366,0.00002886725,0.005382173,0.0001160904,0.00001708148,0.0000824591,0.0001864598,0.0003037564,0.003606674,0.002712673,0.9874007,0.0000286576],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.02479047,0.0007340211,0.03192771,0.008698257,0.005180763,0.001463009,0.778004,0.02800123,0.1212005],"genre_scores_gemma":[0.03031157,0.001008001,0.05570931,0.001777399,0.0008475345,0.001938635,0.8037743,0.01302812,0.09160516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09922642,"threshold_uncertainty_score":0.3319454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02520332210760556,"score_gpt":0.2578297983563138,"score_spread":0.2326264762487082,"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."}}