{"id":"W6956915747","doi":"10.60510/awfwi02928","title":"IGSN AWFWI02928 (EN22071-T09): 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":"Digital Radiography and Breast Imaging","field":"Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0007639541,0.001092886,0.000871582,0.007731268,0.002472827,0.001653142,0.002181103,0.0008339604,0.2044219],"category_scores_gemma":[0.002659945,0.0006858348,0.0003302837,0.0128295,0.0004833003,0.0004994434,0.001516292,0.0007179555,0.1572088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00392592,"about_ca_system_score_gemma":0.01010622,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7444438,"about_ca_topic_score_gemma":0.8647786,"domain_scores_codex":[0.9991797,0.00003220263,0.00005370292,0.0001714308,0.0003264373,0.0002365368],"domain_scores_gemma":[0.9964969,0.0001443847,0.0001795815,0.0004505916,0.00231165,0.0004169155],"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":[0.0001305415,0.00003325324,0.006227029,0.0002876433,0.00001353492,0.00007879081,0.0002875986,0.00009208135,0.001553216,0.0007032031,0.9593704,0.03122273],"study_design_scores_gemma":[0.00003294146,0.00001377579,0.06448442,0.0001389354,0.00002380445,0.0001243226,0.0004075546,0.0001076245,0.0009204939,0.0003541828,0.9333669,0.00002501279],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004815497,0.0001253894,0.0008010416,0.0001042111,0.00005595711,0.0001780925,0.9494221,0.0007562377,0.0437414],"genre_scores_gemma":[0.005601135,0.0001828066,0.00255919,0.000110859,0.00002253645,0.0003014909,0.9172009,0.0008864201,0.07313462],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2555562,"threshold_uncertainty_score":0.6838593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01715250105429961,"score_gpt":0.242109325567045,"score_spread":0.2249568245127453,"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."}}