{"id":"W6919457297","doi":"10.60510/awfwi03595","title":"IGSN AWFWI03595 (EN22058-TG04): Individual Sample (Biology, leaf for DNA analyses) of sample EN22058-T04 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":[0.001698978,0.003263185,0.004836088,0.003312211,0.0003765423,0.0003812531,0.003772852,0.003397817,0.01326676],"category_scores_gemma":[0.005641662,0.003234678,0.002325647,0.00231667,0.00212806,0.00043,0.00172263,0.001853197,0.001836244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008421093,"about_ca_system_score_gemma":0.001216279,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9173223,"about_ca_topic_score_gemma":0.63526,"domain_scores_codex":[0.9866897,0.0008057625,0.003076302,0.004563597,0.001699475,0.003165102],"domain_scores_gemma":[0.9841629,0.006770959,0.002645578,0.004690737,0.0006698745,0.001059995],"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":[0.0004791858,0.000636519,0.002611899,0.001154446,0.00572529,0.00004420328,0.001830708,0.00004411176,0.0001079145,0.001071813,0.9848371,0.001456803],"study_design_scores_gemma":[0.004332447,0.0006206214,0.0007803286,0.001066763,0.004454894,0.00003071198,0.0006063001,0.0001831034,0.001927584,0.02017191,0.9623951,0.003430201],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00211869,0.009750229,0.01850634,0.0001469024,0.002761488,0.003553351,0.9607095,0.001607146,0.000846347],"genre_scores_gemma":[0.01474696,0.000359875,0.03270482,0.0004108575,0.003211416,0.001111701,0.9412013,0.004649071,0.001603992],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2820624,"threshold_uncertainty_score":0.9989409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07895798275516376,"score_gpt":0.340493188318793,"score_spread":0.2615352055636292,"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."}}