{"id":"W6900551965","doi":"10.60510/awfwi02981","title":"IGSN AWFWI02981 (EN22002-TG08): Individual Sample (Biology, leaf for DNA analyses) of sample EN22002-T08 from Takhini River, 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; Analytical Chemistry (journal); Sample preparation","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001202653,0.002009128,0.001541494,0.006790964,0.002710985,0.001628512,0.003133221,0.001608145,0.1442364],"category_scores_gemma":[0.002253758,0.00109612,0.0007904217,0.01276218,0.0006097566,0.0009624748,0.002129961,0.001099713,0.156088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002022949,"about_ca_system_score_gemma":0.005482864,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.087372,"about_ca_topic_score_gemma":0.2007967,"domain_scores_codex":[0.9987981,0.00005983841,0.000111679,0.0004906824,0.000268377,0.0002712729],"domain_scores_gemma":[0.998385,0.000116303,0.0001424846,0.0005532972,0.0005756301,0.0002272804],"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":[0.0005277619,0.0001151865,0.0115884,0.001694156,0.0001202713,0.0003450757,0.001433146,0.0003836095,0.02094691,0.003638073,0.8992316,0.05997586],"study_design_scores_gemma":[0.0000589571,0.00002763632,0.02964354,0.000157236,0.0001010501,0.0001866031,0.0002910989,0.0001269438,0.003215446,0.00100156,0.9651474,0.00004247804],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003319251,0.00007924381,0.002960522,0.00004695022,0.00005631309,0.0001306248,0.9742751,0.001863524,0.01726852],"genre_scores_gemma":[0.002670032,0.00006024765,0.003732534,0.00006630472,0.000009119739,0.0002803533,0.9824207,0.001593841,0.009166822],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.912628,"threshold_uncertainty_score":0.4825189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0918449674464523,"score_gpt":0.3466627733101263,"score_spread":0.254817805863674,"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."}}