{"id":"W6956786876","doi":"10.60510/awfwi02949","title":"IGSN AWFWI02949 (EN22072-T04): Individual Sample (Biology, plant - Pinus contorta) 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); Pinus <genus>; Hydrology (agriculture); Dendrochronology; Vegetation (pathology)","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":[0.001066851,0.001736755,0.001588239,0.01189678,0.003451304,0.002467146,0.002977808,0.00138449,0.1854545],"category_scores_gemma":[0.004210777,0.001041055,0.0005315953,0.02502186,0.0005748903,0.0008206735,0.001939366,0.001258128,0.1246945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005280983,"about_ca_system_score_gemma":0.014747,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.800335,"about_ca_topic_score_gemma":0.8855178,"domain_scores_codex":[0.9988612,0.00004841064,0.00008528765,0.0002876993,0.0003424081,0.0003750569],"domain_scores_gemma":[0.9965996,0.0002419796,0.0002541942,0.0005711277,0.001817656,0.0005153537],"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":[0.00009856533,0.0000164555,0.002745924,0.0004116586,0.00002496944,0.00005684501,0.0002592271,0.00009474299,0.0004981664,0.0005315383,0.9852748,0.009987063],"study_design_scores_gemma":[0.00005742084,0.000009309817,0.03827989,0.0003046832,0.00005409416,0.00007765053,0.0003202866,0.00008033546,0.0004551525,0.0004840018,0.9598444,0.0000328516],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008537351,0.00007574089,0.0002366378,0.00003081726,0.00002655015,0.00004122311,0.9901859,0.0003681754,0.0081813],"genre_scores_gemma":[0.001767402,0.0001193261,0.0008659562,0.00005833034,0.000009921279,0.0001803227,0.981339,0.0005735902,0.01508613],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.199665,"threshold_uncertainty_score":0.6204072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0253559438309306,"score_gpt":0.2487837272901555,"score_spread":0.2234277834592249,"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."}}