{"id":"W6930659110","doi":"10.5281/zenodo.15295544","title":"Diversité des langues turques en Asie Centrale","year":2024,"lang":"fr","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Cancer, Lipids, and Metabolism","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"South asia; Protectorate; Context (archaeology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002655755,0.0001853565,0.0002409298,0.001608719,0.0008089383,0.00102307,0.0002063849,0.0001497823,0.004048047],"category_scores_gemma":[0.000440356,0.0001022841,0.0001662146,0.001634993,0.0007280337,0.0003712914,0.0008306033,0.0002515794,0.0003108457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001099841,"about_ca_system_score_gemma":0.001140955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07957211,"about_ca_topic_score_gemma":0.1471993,"domain_scores_codex":[0.9998643,0.00002158027,0.000007621854,0.00003475317,0.00001830298,0.00005337223],"domain_scores_gemma":[0.9996527,0.00004107616,0.00008511543,0.00001955097,0.0001208511,0.00008071735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003899925,0.0000422118,0.8902342,0.0003861366,0.0001337878,0.000781675,0.02661628,0.001210038,0.01298423,0.006662279,0.002233452,0.05832563],"study_design_scores_gemma":[0.0000132025,0.00005971636,0.9788297,0.0000501436,0.00002028531,0.0003264639,0.007503816,0.0004021235,0.0003065692,0.0002620348,0.01221157,0.00001430121],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948001,0.0004834393,0.00006067425,0.0001000004,0.000006687792,0.000006222019,0.0003359019,0.00001920157,0.004187818],"genre_scores_gemma":[0.9974837,0.0002499358,0.0001044963,0.00001752358,0.000004782773,0.00000786512,0.0002034026,0.00000288326,0.001925478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07957211,"threshold_uncertainty_score":0.1582179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01757202587508878,"score_gpt":0.2391350290859743,"score_spread":0.2215630032108856,"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."}}