{"id":"W6969202344","doi":"10.5281/zenodo.4765430","title":"Isoperla montana","year":2017,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Freshwater macroinvertebrate diversity and ecology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Spring (device); Holotype; Mill; Clockwise; Terrace (agriculture)","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":[0.0001125477,0.0007589944,0.0002258343,0.00204812,0.00191316,0.0006317523,0.0004869412,0.0005640395,0.03335159],"category_scores_gemma":[0.0002364706,0.0002679793,0.0002565161,0.0005880828,0.000436141,0.0009962295,0.0009206276,0.0006417751,0.01143704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001026053,"about_ca_system_score_gemma":0.000504807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01861718,"about_ca_topic_score_gemma":0.04629629,"domain_scores_codex":[0.9998641,0.00001606535,0.00000828625,0.00005509564,0.0000343638,0.00002208167],"domain_scores_gemma":[0.9998606,0.00001739739,0.00004781387,0.00001403878,0.0000445089,0.00001561501],"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":[0.0004217733,0.0001648421,0.01770775,0.00121206,0.00005312516,0.002116476,0.002266969,0.0002680665,0.07185136,0.01001312,0.2114109,0.6825135],"study_design_scores_gemma":[0.00003822441,0.0001239371,0.1023045,0.0007207439,0.00005805017,0.00321014,0.001161557,0.0001792929,0.003130432,0.00162474,0.8874147,0.00003349864],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1335281,0.02285851,0.003867128,0.003404676,0.0008387821,0.0004200577,0.005634505,0.001613151,0.827835],"genre_scores_gemma":[0.733863,0.01026784,0.01413524,0.007418775,0.0007378486,0.0004673945,0.01078749,0.0003131502,0.2220092],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03335159,"threshold_uncertainty_score":0.1115722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03040972237067195,"score_gpt":0.2159855416874426,"score_spread":0.1855758193167706,"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."}}