{"id":"W6956464612","doi":"10.60510/awfwi03310","title":"IGSN AWFWI03310 (EN22028-TG01): Individual Sample (Biology, leaf for DNA analyses) of sample EN22028-T01 from Peel River Watershed, Northwest Territories, CA","year":2024,"lang":"en","type":"other","venue":"GFZ IGSN Sample Catalogue","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Sample (material); DNA; Quality (philosophy)","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":[],"consensus_categories":[],"category_scores_codex":[0.001371695,0.00175861,0.001198233,0.005929453,0.002141007,0.001658608,0.003118131,0.001392739,0.2126557],"category_scores_gemma":[0.002665751,0.001003214,0.000588629,0.01062712,0.0005315188,0.0008792455,0.001907081,0.001006088,0.2306176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002117184,"about_ca_system_score_gemma":0.004600997,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1210649,"about_ca_topic_score_gemma":0.2148438,"domain_scores_codex":[0.9989328,0.00006386977,0.00007084411,0.000361762,0.0003404557,0.0002302576],"domain_scores_gemma":[0.9981108,0.0001850649,0.0001725306,0.000570577,0.0006898887,0.0002712256],"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":[0.0002554276,0.00006657255,0.00337548,0.0005208438,0.00003002918,0.00008523972,0.0003236681,0.0002377922,0.008531182,0.00209351,0.9441282,0.04035206],"study_design_scores_gemma":[0.00005653283,0.00001971114,0.0139293,0.0001288676,0.00003477944,0.0000994264,0.0001328901,0.0002136096,0.004445049,0.0009907363,0.9799209,0.0000281652],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002796927,0.00006241578,0.0033965,0.00007107233,0.00005095637,0.0001176543,0.953979,0.003459083,0.03606647],"genre_scores_gemma":[0.002071812,0.00006627031,0.005698153,0.00007906768,0.000014039,0.0002580113,0.9747713,0.002814544,0.0142268],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8789351,"threshold_uncertainty_score":0.7114041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04125852703712547,"score_gpt":0.2939535159352692,"score_spread":0.2526949888981437,"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."}}