{"id":"W6919461203","doi":"10.60510/awfwi02905","title":"IGSN AWFWI02905 (EN22069-T19): Individual Sample (Biology, plant - Betula glandulosa) from Fort Nelson - T8 Area East, 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); Vegetation (pathology); Work (physics)","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":[0.001021263,0.001699619,0.001562108,0.0119396,0.003655179,0.002401157,0.002899444,0.001378426,0.1693856],"category_scores_gemma":[0.003879233,0.0009081388,0.0005191542,0.02484732,0.000590861,0.0008075809,0.001962199,0.001208315,0.1497836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004786505,"about_ca_system_score_gemma":0.01223571,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7025501,"about_ca_topic_score_gemma":0.8272175,"domain_scores_codex":[0.9988312,0.00004353864,0.00008182582,0.0002913037,0.0003855969,0.0003665962],"domain_scores_gemma":[0.9965579,0.0002159624,0.0002493028,0.0006150717,0.001849728,0.0005119588],"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":[0.000121884,0.00001916444,0.003019779,0.0004381793,0.00002609865,0.00006827262,0.000298065,0.00009350576,0.000975952,0.0007213327,0.9815109,0.0127069],"study_design_scores_gemma":[0.00003865172,0.000008586826,0.03132004,0.0002074501,0.00004437777,0.00007627545,0.0002677287,0.00005848872,0.0005427229,0.0004562565,0.9669527,0.00002652334],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001228479,0.0000880594,0.0003253545,0.00003467748,0.00003386475,0.00004547749,0.9859216,0.0004912187,0.01183129],"genre_scores_gemma":[0.001965065,0.0001263954,0.0010593,0.00006053985,0.00001165032,0.0001617859,0.9794629,0.0006820448,0.01647039],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8306144,"threshold_uncertainty_score":0.5984032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0385381789560087,"score_gpt":0.2517465948577979,"score_spread":0.2132084159017892,"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."}}