{"id":"W6900678009","doi":"10.60510/awfwi03677","title":"IGSN AWFWI03677 (EN22064-TG03): Individual Sample (Biology, leaf for DNA analyses) of sample EN22064-T03 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":[0.001520756,0.002094332,0.001775052,0.008892082,0.00441205,0.002681193,0.003920894,0.001972373,0.2039028],"category_scores_gemma":[0.003276065,0.001311788,0.0006548398,0.01549994,0.0008058505,0.0008995844,0.0022033,0.001661437,0.1911795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004271243,"about_ca_system_score_gemma":0.01069883,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3989952,"about_ca_topic_score_gemma":0.6741505,"domain_scores_codex":[0.9986065,0.00006649837,0.00009299428,0.0004400758,0.0004685831,0.000325388],"domain_scores_gemma":[0.9977215,0.0001958609,0.0001603035,0.0005823729,0.0009267355,0.0004131202],"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":[0.0002472069,0.00005061119,0.003381705,0.0007123481,0.00004413797,0.0001775642,0.0006464756,0.0001940677,0.007820797,0.002189087,0.9501101,0.03442589],"study_design_scores_gemma":[0.00005426196,0.00001523775,0.01429408,0.000239709,0.00005612153,0.0001451188,0.0001866745,0.0001052686,0.002302078,0.001004376,0.9815561,0.00004104122],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002835626,0.0001475323,0.002741657,0.00009189248,0.00007850788,0.0001669752,0.9551791,0.002668777,0.03608996],"genre_scores_gemma":[0.002985904,0.0001516562,0.004739122,0.0001529009,0.00001680816,0.000376912,0.9597661,0.003101448,0.0287091],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7960972,"threshold_uncertainty_score":0.7933456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06164588891695874,"score_gpt":0.3183490318328885,"score_spread":0.2567031429159298,"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."}}