{"id":"W6931085783","doi":"10.5281/zenodo.4366904","title":"Toxicodendron pubescens Mill.","year":2007,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Clementine (nuclear reactor); Sinkhole; Context (archaeology)","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":[0.0001198787,0.0009181696,0.0004874834,0.00188743,0.001028716,0.0003912984,0.0005165979,0.0002138013,0.02456396],"category_scores_gemma":[0.0002611351,0.000165448,0.0001664492,0.001519487,0.0001871391,0.0008705122,0.0006405102,0.000444872,0.01975044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005657341,"about_ca_system_score_gemma":0.0002973739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01724501,"about_ca_topic_score_gemma":0.03897613,"domain_scores_codex":[0.9998752,0.000008221622,0.000008713112,0.00004779314,0.00004225178,0.00001783367],"domain_scores_gemma":[0.9998176,0.00002209798,0.00005915051,0.00001740254,0.00004280905,0.0000411146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001611533,0.0004817514,0.05048003,0.001365135,0.0001266899,0.005143378,0.001211652,0.000644775,0.2727946,0.002458833,0.09613634,0.5675453],"study_design_scores_gemma":[0.0001023676,0.000286513,0.4236034,0.000142938,0.0001329289,0.00627457,0.0009697954,0.0003547098,0.01505209,0.001084077,0.5519498,0.00004683505],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2801724,0.0108202,0.006278678,0.001224115,0.001026966,0.0006707819,0.06840549,0.004146683,0.6272547],"genre_scores_gemma":[0.7839708,0.004800216,0.00469809,0.0008813738,0.000251975,0.0002077253,0.02381811,0.0003272372,0.1810444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02456396,"threshold_uncertainty_score":0.08217466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02944757990477796,"score_gpt":0.2504602047545597,"score_spread":0.2210126248497818,"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."}}