{"id":"W6957187167","doi":"10.60510/awfwi03594","title":"IGSN AWFWI03594 (EN22058-TG03): Individual Sample (Biology, leaf for DNA analyses) of sample EN22058-T03 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":[0.001687317,0.003256135,0.004849273,0.003368423,0.000374792,0.0003812068,0.003751398,0.00338609,0.01047568],"category_scores_gemma":[0.005587198,0.003230354,0.002304112,0.002331573,0.002105344,0.0004291534,0.001661094,0.001844639,0.001276215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008204372,"about_ca_system_score_gemma":0.001204966,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.916274,"about_ca_topic_score_gemma":0.6246181,"domain_scores_codex":[0.986703,0.0008171726,0.003075616,0.004560447,0.001683425,0.003160318],"domain_scores_gemma":[0.9842719,0.006628532,0.002642507,0.004725414,0.0006707144,0.001060895],"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":[0.0004721464,0.0006448724,0.002965797,0.001128643,0.005838086,0.00004404079,0.001773176,0.00005135714,0.0001023374,0.001213572,0.9840853,0.001680628],"study_design_scores_gemma":[0.004351525,0.0006285433,0.0008472761,0.001042555,0.004571169,0.00003133939,0.0006091767,0.0002328118,0.001743684,0.02076732,0.9617277,0.003446901],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002237503,0.009267115,0.01963011,0.0001406631,0.002806308,0.003528072,0.960067,0.001613486,0.0007097216],"genre_scores_gemma":[0.01749622,0.00033637,0.02926394,0.0004146817,0.00322735,0.001110727,0.9421636,0.00468547,0.001301639],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2916559,"threshold_uncertainty_score":0.9995014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07886903491071029,"score_gpt":0.3403920587008262,"score_spread":0.2615230237901159,"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."}}