{"id":"W6938361647","doi":"10.60510/awfwi03610","title":"IGSN AWFWI03610 (EN22059-TG03): Individual Sample (Biology, leaf for DNA analyses) of sample EN22059-T03 from Nordenskiold 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":[0.001550594,0.003191297,0.004771116,0.003180328,0.0003553993,0.0003608305,0.003738792,0.003264918,0.01093495],"category_scores_gemma":[0.006112494,0.003130037,0.002261656,0.002216888,0.002076375,0.0003518763,0.001696953,0.001847175,0.001315578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007238691,"about_ca_system_score_gemma":0.001142969,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9185023,"about_ca_topic_score_gemma":0.6964304,"domain_scores_codex":[0.9871528,0.0007251091,0.003013384,0.004437699,0.001583412,0.003087662],"domain_scores_gemma":[0.9841201,0.006964307,0.002522029,0.004662731,0.0007048523,0.001025958],"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":[0.0004169552,0.0005748417,0.004101224,0.001065543,0.005541248,0.00004206502,0.001525101,0.00004670019,0.00009727566,0.0009716387,0.9845762,0.001041256],"study_design_scores_gemma":[0.004043231,0.000540775,0.0007024952,0.0009620175,0.004188186,0.00002897604,0.0004820915,0.0001627429,0.001433287,0.01642892,0.9677359,0.003291419],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002423305,0.008694796,0.01454369,0.0001417786,0.002775434,0.003342492,0.9659411,0.001508374,0.0006290894],"genre_scores_gemma":[0.01373813,0.0003226563,0.0325081,0.0004157189,0.003266265,0.001008797,0.942548,0.004553056,0.001639285],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2220719,"threshold_uncertainty_score":0.999462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07459075180456018,"score_gpt":0.3371218647924422,"score_spread":0.262531112987882,"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."}}