{"id":"W6931588702","doi":"10.5281/zenodo.5679778","title":"Ablabesmyia (Asayia) annulata Say","year":2011,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Beaver; Fishing; Pupa; Mile; Larva","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006885273,0.0001331319,0.0001205468,0.000185357,0.001582312,0.000688816,0.002389602,0.00005135274,0.006983938],"category_scores_gemma":[0.0002915005,0.0001335716,0.00004762892,0.000611289,0.00009172868,0.0004838373,0.001790539,0.0003029095,0.01253649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004475154,"about_ca_system_score_gemma":0.000003287872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000357795,"about_ca_topic_score_gemma":1.119645e-7,"domain_scores_codex":[0.9983233,0.0002957974,0.0001910509,0.0004762335,0.0003287752,0.0003848767],"domain_scores_gemma":[0.9986242,0.00001544169,0.00008364153,0.0007825898,0.0002998178,0.0001942951],"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":[0.00002416081,0.0002685598,0.00003201401,0.00003926785,0.0000517939,0.00007272178,0.005726716,0.00004929677,0.001179751,0.09967028,0.2276082,0.6652772],"study_design_scores_gemma":[0.000298041,0.0002164999,0.0022085,0.00001547331,0.000004649801,0.0001341294,0.00006082921,0.009750242,0.0004244353,0.001244751,0.9854289,0.000213526],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.006299772,0.0001222786,0.3689551,0.001367079,0.0003759773,0.0003227543,0.00004313824,0.003408862,0.619105],"genre_scores_gemma":[0.9562382,0.00007646771,0.03359389,0.000862813,0.0003804539,5.585136e-8,0.0004433918,0.001721579,0.006683129],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9499384,"threshold_uncertainty_score":0.9997175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0437387871910469,"score_gpt":0.2378639850743917,"score_spread":0.1941251978833448,"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."}}