{"id":"W6938265040","doi":"10.60510/awfwi03604","title":"IGSN AWFWI03604 (EN22058-TG13): Individual Sample (Biology, leaf for DNA analyses) of sample EN22058-T13 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":[0.001676609,0.00326454,0.004838582,0.003344342,0.0003722138,0.0003802543,0.003770568,0.003392759,0.01058102],"category_scores_gemma":[0.005765543,0.003233475,0.002306543,0.002329585,0.002086384,0.0004335678,0.001726651,0.001849897,0.001541668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008295419,"about_ca_system_score_gemma":0.001189845,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9231874,"about_ca_topic_score_gemma":0.6339234,"domain_scores_codex":[0.9866874,0.0008039483,0.003086802,0.00456129,0.001694093,0.003166456],"domain_scores_gemma":[0.9841443,0.006781137,0.002645165,0.00468962,0.0006786528,0.001061175],"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":[0.0004760743,0.0006308039,0.002767282,0.001162376,0.005739068,0.00004338404,0.001900717,0.00005656094,0.0001127757,0.001258717,0.9843971,0.001455119],"study_design_scores_gemma":[0.004374402,0.0006212068,0.0008672436,0.001073053,0.004449074,0.00003088898,0.0006151495,0.0002229831,0.002006485,0.02126172,0.960997,0.003480757],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00241691,0.009612068,0.01912244,0.0001621883,0.002756818,0.003511174,0.9601774,0.001605451,0.0006355547],"genre_scores_gemma":[0.01841207,0.0003619419,0.03275711,0.0004140199,0.003245216,0.001101519,0.9377884,0.004626322,0.001293385],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.289264,"threshold_uncertainty_score":0.9992357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07868333218718844,"score_gpt":0.3399589237828339,"score_spread":0.2612755915956455,"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."}}