{"id":"W6912836141","doi":"10.5281/zenodo.5965646","title":"Hydrellia griseola","year":2018,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Marine Biology and Ecology Research","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chine; China; Fish pond; Leaf spot","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":[0.0001032599,0.0006373482,0.0002898708,0.001113661,0.001043434,0.0003252268,0.0004301044,0.000541173,0.01313673],"category_scores_gemma":[0.0003188782,0.0002155031,0.0001823553,0.0005445212,0.000442229,0.001045343,0.001000672,0.0004888079,0.00363598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000645565,"about_ca_system_score_gemma":0.0002229659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007517458,"about_ca_topic_score_gemma":0.013469,"domain_scores_codex":[0.9998716,0.00001853782,0.00001104993,0.00004855555,0.00002741056,0.00002282435],"domain_scores_gemma":[0.9998732,0.00002631948,0.00003999074,0.00001178242,0.00002630138,0.00002230303],"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":[0.001087369,0.0002730222,0.103564,0.002329642,0.0001277185,0.009557934,0.004707757,0.002126577,0.1159959,0.005342925,0.03100123,0.7238861],"study_design_scores_gemma":[0.0001442342,0.0003123891,0.6323414,0.0005465868,0.00007365578,0.01168675,0.002004943,0.0007986876,0.005640544,0.001867886,0.344532,0.00005096175],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6931883,0.01338559,0.003036848,0.001001329,0.0004900721,0.0004370165,0.007713351,0.0006609255,0.2800866],"genre_scores_gemma":[0.9705189,0.002405556,0.001984817,0.0005936131,0.000106722,0.0000910689,0.002587085,0.00002247493,0.02168977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01313673,"threshold_uncertainty_score":0.04394668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03181785791776413,"score_gpt":0.2307837997428326,"score_spread":0.1989659418250685,"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."}}