{"id":"W6912719441","doi":"10.5281/zenodo.7837174","title":"Trimerotropis verruculata subsp. verruculata","year":2023,"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":"Subspecies; Natural (archaeology); Period (music); Holotype","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":[0.0001228313,0.0005148023,0.0003407953,0.001021473,0.001133627,0.000429122,0.0008273157,0.0004301169,0.01164657],"category_scores_gemma":[0.0002970072,0.0001547182,0.0001733215,0.0005414694,0.0003079462,0.0006410892,0.00110895,0.0003208805,0.004038457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003760579,"about_ca_system_score_gemma":0.0002105911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0117016,"about_ca_topic_score_gemma":0.02219745,"domain_scores_codex":[0.9998574,0.00001342855,0.00001196512,0.00004846262,0.00003192245,0.00003680869],"domain_scores_gemma":[0.9998822,0.00001183661,0.00004447948,0.00001651371,0.00002744732,0.00001757832],"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":[0.0007213419,0.0004313065,0.08599149,0.0008009786,0.0001293366,0.005160065,0.002930414,0.001162371,0.1609916,0.002773192,0.01948082,0.719427],"study_design_scores_gemma":[0.00008008757,0.0005714942,0.7404243,0.0004630423,0.0001216096,0.0100697,0.002634143,0.002187642,0.007894133,0.0013207,0.2341804,0.00005282582],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.724138,0.007351602,0.003915974,0.0004327564,0.0003403198,0.0002658055,0.002420798,0.0007349072,0.2603998],"genre_scores_gemma":[0.973692,0.001600342,0.002062388,0.0003961885,0.0000777458,0.00009234145,0.002432194,0.0000365909,0.01961017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0117016,"threshold_uncertainty_score":0.03896165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03740375621402699,"score_gpt":0.2199018069982732,"score_spread":0.1824980507842462,"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."}}