{"id":"W6893851390","doi":"10.5281/zenodo.4920627","title":"Lesteva schoenmanni Shavrin 2017, sp.n.","year":2017,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Holotype; Sternum; Paratype; Arthropod mouthparts; Aedeagus","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":[0.0001828935,0.0008157899,0.0003711929,0.001480615,0.001713802,0.0006624451,0.000573539,0.0005957579,0.0116842],"category_scores_gemma":[0.0005837147,0.0002911077,0.000191099,0.000841764,0.0006985116,0.001852604,0.00117252,0.0007116022,0.004962153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006832721,"about_ca_system_score_gemma":0.0004067319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008275632,"about_ca_topic_score_gemma":0.01953223,"domain_scores_codex":[0.9998149,0.00003067811,0.00001695785,0.00006733558,0.00005189425,0.0000183162],"domain_scores_gemma":[0.9998314,0.00004315832,0.00006093431,0.0000200801,0.00003135942,0.00001302812],"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":[0.0004999709,0.000124352,0.02687584,0.001519801,0.0001320889,0.003865155,0.005401741,0.003532963,0.0286497,0.01779018,0.06626248,0.8453458],"study_design_scores_gemma":[0.00009957716,0.0001819112,0.180425,0.001070715,0.0001570603,0.01089425,0.002912601,0.001507818,0.003840656,0.005676629,0.7931727,0.00006105127],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2933082,0.03470537,0.01390134,0.001730333,0.001015253,0.0006160166,0.006592562,0.001629564,0.6465014],"genre_scores_gemma":[0.9182516,0.005514045,0.00731287,0.0007795333,0.0003223947,0.0002744406,0.003151264,0.0001100716,0.06428382],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0116842,"threshold_uncertainty_score":0.03908759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06770884651006026,"score_gpt":0.2409844269117039,"score_spread":0.1732755804016437,"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."}}