{"id":"W6919198341","doi":"10.60510/awfwi02946","title":"IGSN AWFWI02946 (EN22072-T01): Individual Sample (Biology, plant - Abies lasiocarpa) from Fort Nelson River lowlands, 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); Hydrology (agriculture); Vegetation (pathology); Population","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":[0.001154271,0.00166375,0.001558332,0.01138063,0.003745883,0.002469145,0.003003141,0.001308567,0.1520178],"category_scores_gemma":[0.004017305,0.001015144,0.0005150484,0.02449535,0.000586457,0.0007430617,0.001836864,0.001299001,0.1111335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005376766,"about_ca_system_score_gemma":0.01515056,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7912212,"about_ca_topic_score_gemma":0.8865952,"domain_scores_codex":[0.9987549,0.00005275308,0.00009544381,0.0003046304,0.0004035128,0.0003888172],"domain_scores_gemma":[0.9963533,0.0002348464,0.0002610932,0.0006281987,0.00199783,0.0005248507],"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":[0.0001319332,0.00002500392,0.004121589,0.0004510019,0.00003118633,0.00007463738,0.0003858878,0.0001117128,0.0008892582,0.0006903436,0.9795775,0.01350997],"study_design_scores_gemma":[0.00005880486,0.00001110103,0.04643353,0.00025651,0.00005622721,0.0000833161,0.0003807286,0.00008235289,0.0005567535,0.0004822847,0.9515652,0.00003322449],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001378228,0.000079285,0.0003270807,0.00003510314,0.00002894939,0.00005642753,0.987974,0.00038253,0.009738429],"genre_scores_gemma":[0.002154399,0.0001209232,0.001122332,0.00006044037,0.00001002722,0.0002263767,0.9790964,0.0005550334,0.01665405],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8479822,"threshold_uncertainty_score":0.5085503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02474231612007511,"score_gpt":0.2466855710957253,"score_spread":0.2219432549756502,"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."}}