{"id":"W4394071307","doi":"10.6084/m9.figshare.20415819","title":"Malaise_trap_ReadME.txt","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Trap (plumbing); Malaise; Geography; Meteorology; Medicine","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001302263,0.00146049,0.001211918,0.003553016,0.0009148961,0.002873911,0.001987922,0.001287125,0.584658],"category_scores_gemma":[0.00726804,0.001136401,0.0007546142,0.003352919,0.0003416073,0.002121922,0.002488432,0.0015293,0.4304345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001414912,"about_ca_system_score_gemma":0.001177941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009472559,"about_ca_topic_score_gemma":0.00985295,"domain_scores_codex":[0.9990873,0.0001023586,0.0001259595,0.0002223503,0.0002984098,0.0001634865],"domain_scores_gemma":[0.9928616,0.002306431,0.0008293721,0.001465593,0.002067613,0.0004694212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001189958,0.00002672533,0.001235017,0.0003907009,0.00001500975,0.00002534119,0.000053138,0.00008734679,0.0003432266,0.0004064248,0.9905981,0.006700063],"study_design_scores_gemma":[0.0002129731,0.00002910008,0.01341872,0.0001843558,0.00001451029,0.00003533462,0.00008406906,0.000254386,0.001623321,0.0008139139,0.9832872,0.00004205576],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003123833,0.00001629979,0.000262169,0.0001357538,0.00007106549,0.00004769992,0.9908505,0.004366145,0.003937872],"genre_scores_gemma":[0.002621242,0.00004749243,0.001418316,0.0002825225,0.00009039836,0.0006144248,0.9757668,0.005573179,0.0135856],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.415342,"threshold_uncertainty_score":0.592435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02037946096692176,"score_gpt":0.2855029548047442,"score_spread":0.2651234938378225,"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."}}