{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001556411,0.000417763,0.0002841699,0.0007541009,0.001116618,0.0002444774,0.0002392245,0.0003484177,0.008318476],"category_scores_gemma":[0.0001520246,0.0001269132,0.0001797445,0.0005097808,0.0003488315,0.0005714673,0.0005763845,0.000490925,0.004343525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003156941,"about_ca_system_score_gemma":0.000157865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005857558,"about_ca_topic_score_gemma":0.01413453,"domain_scores_codex":[0.9999034,0.00000850207,0.00001048637,0.0000352266,0.0000231975,0.00001911044],"domain_scores_gemma":[0.9999177,0.00001211825,0.00002560124,0.000006457267,0.0000211637,0.00001685214],"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":[0.001538032,0.000382926,0.09648348,0.001140576,0.0001086312,0.004282415,0.004755515,0.002555294,0.2924168,0.008706649,0.02152384,0.5661059],"study_design_scores_gemma":[0.0001608392,0.001242807,0.6515967,0.0003419321,0.0001640914,0.005487386,0.004349034,0.001709867,0.01185439,0.002733705,0.3202891,0.00007013655],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8576165,0.003543972,0.003833249,0.0004571361,0.0003172393,0.0001235557,0.002887212,0.0004223615,0.1307987],"genre_scores_gemma":[0.9685017,0.001253779,0.002851642,0.0004122769,0.000120969,0.00007420067,0.001507163,0.00001692484,0.02526128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008318476,"threshold_uncertainty_score":0.0278281,"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."}}