{"id":"W6900546067","doi":"10.60510/awfwi03673","title":"IGSN AWFWI03673 (EN22063-TG20): Individual Sample (Biology, leaf for DNA analyses) of sample EN22063-T20 from Liard River, British Columbia, 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; Sample size determination","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":[0.001472922,0.002142023,0.001743046,0.008331208,0.0043614,0.002504784,0.003840183,0.002039714,0.2009275],"category_scores_gemma":[0.002886861,0.00129567,0.000658319,0.01353566,0.0007876817,0.0008868217,0.002198456,0.001576653,0.1746488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003898265,"about_ca_system_score_gemma":0.008988122,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3393243,"about_ca_topic_score_gemma":0.6331916,"domain_scores_codex":[0.9987034,0.00005786779,0.00008529125,0.0004339737,0.0004273393,0.0002922695],"domain_scores_gemma":[0.9981322,0.0001699054,0.0001365396,0.0004846401,0.0007152418,0.0003614931],"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":[0.0002925784,0.0000599677,0.003843664,0.0008328847,0.00005219468,0.0002561213,0.000785751,0.0002231745,0.0118891,0.002782038,0.9392482,0.03973419],"study_design_scores_gemma":[0.0000592287,0.00001706291,0.01491882,0.0002526777,0.0000632514,0.0001904692,0.0001848926,0.0001136801,0.002775667,0.001090455,0.9802917,0.00004221476],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003561887,0.000179171,0.003698646,0.0001027653,0.00008942507,0.0001933227,0.9475315,0.003176576,0.0414667],"genre_scores_gemma":[0.003729371,0.0001803478,0.005571639,0.0001828215,0.00001803596,0.0004239466,0.9545984,0.003709682,0.03158572],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7990724,"threshold_uncertainty_score":0.6746984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06178717474294261,"score_gpt":0.3182620645253066,"score_spread":0.256474889782364,"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."}}