{"id":"W6931392167","doi":"10.5281/zenodo.4368159","title":"Boehmeria cylindrica Sw.","year":2007,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Capitata; Oleaceae; Urticaceae; Subspecies; Folk medicine","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":[0.0001220977,0.001068409,0.0005605,0.002263516,0.001241898,0.0003566548,0.000736056,0.0004023093,0.01928745],"category_scores_gemma":[0.0003259426,0.0002952694,0.000232246,0.001292324,0.0002075393,0.0006139094,0.000620229,0.0005123287,0.01493227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001041774,"about_ca_system_score_gemma":0.0002425904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02940858,"about_ca_topic_score_gemma":0.08228078,"domain_scores_codex":[0.9997765,0.00001889023,0.00001072239,0.00009523516,0.00006835336,0.00003017988],"domain_scores_gemma":[0.9998834,0.00001393388,0.00002874351,0.00001606494,0.00003700468,0.00002089222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005437566,0.0001594437,0.01132175,0.001007099,0.00008001844,0.001136902,0.0008844248,0.0005382058,0.3005923,0.004600328,0.0846513,0.5944845],"study_design_scores_gemma":[0.00004938021,0.0001213598,0.1871952,0.000141813,0.00009159094,0.002597535,0.0004159121,0.0004399695,0.01392122,0.0008023279,0.7941821,0.00004158794],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1783657,0.04854717,0.01295834,0.002086879,0.001019916,0.001017667,0.02575589,0.005539434,0.7247089],"genre_scores_gemma":[0.7681107,0.008676157,0.0115829,0.001464884,0.0002297638,0.0003621686,0.01492808,0.0005379006,0.1941075],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02940858,"threshold_uncertainty_score":0.06452292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09482648186620563,"score_gpt":0.3459640705741835,"score_spread":0.2511375887079779,"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."}}