{"id":"W6900391335","doi":"10.60510/awfwi03603","title":"IGSN AWFWI03603 (EN22058-TG12): Individual Sample (Biology, leaf for DNA analyses) of sample EN22058-T12 from Yukon River Lowlands, Yukon, CA","year":2024,"lang":"en","type":"other","venue":"GFZ IGSN Sample Catalogue","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Sample (material); DNA","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.001719933,0.003260785,0.004833416,0.003379326,0.0003710053,0.0003719804,0.003728206,0.003393111,0.01096873],"category_scores_gemma":[0.00572391,0.003231411,0.002325518,0.002314241,0.002091449,0.0004370522,0.001752729,0.001847503,0.001545968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008175048,"about_ca_system_score_gemma":0.001155329,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9071842,"about_ca_topic_score_gemma":0.6173304,"domain_scores_codex":[0.9866895,0.0008263494,0.003083243,0.004532536,0.001689056,0.003179295],"domain_scores_gemma":[0.9840601,0.006892018,0.002645018,0.004674899,0.000663923,0.001064023],"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":[0.0004922214,0.0006410523,0.003474776,0.001153102,0.005775775,0.00004289075,0.001816814,0.00005232059,0.000104403,0.001340155,0.9835931,0.001513395],"study_design_scores_gemma":[0.00426417,0.0006054565,0.0007946555,0.001023345,0.004421374,0.00003054151,0.0005680782,0.0002066439,0.001973654,0.02139175,0.9613032,0.003417178],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002524979,0.009856204,0.01926748,0.0001513947,0.002753542,0.00348207,0.9596819,0.001585047,0.0006974084],"genre_scores_gemma":[0.01579767,0.0003604055,0.03299231,0.0004571211,0.003261334,0.00108958,0.9400735,0.004606294,0.001361793],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2898538,"threshold_uncertainty_score":0.9992315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07986746650325979,"score_gpt":0.3407082814543026,"score_spread":0.2608408149510428,"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."}}