{"id":"W7071109841","doi":"","title":"Rehearsal Vienna VCI talk Peter Schade","year":2010,"lang":"en","type":"other","venue":"International Linear Collider","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Czech; Phone; Bridge (graph theory); Special section; Kingdom","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":[0.001020947,0.001323989,0.0006290672,0.0009966969,0.002608624,0.00448971,0.001260893,0.001697527,0.7732677],"category_scores_gemma":[0.002953022,0.0005673541,0.0006378249,0.0005139486,0.0005945003,0.002938458,0.004038035,0.003928286,0.7059282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001375391,"about_ca_system_score_gemma":0.001707608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003260335,"about_ca_topic_score_gemma":0.01037926,"domain_scores_codex":[0.9992144,0.00008804992,0.00002657495,0.0001265397,0.0003741627,0.0001702741],"domain_scores_gemma":[0.9987293,0.00008491176,0.00003412833,0.0001202546,0.000503881,0.0005274675],"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":[0.00002327498,0.00001202907,0.00002067007,0.00001906378,6.889562e-7,0.00001596128,0.00005094109,0.00002197721,0.0001999256,0.0009418811,0.9855461,0.01314732],"study_design_scores_gemma":[0.000005517811,0.0000141833,0.0001947192,0.00004354085,0.000001303224,0.00003739789,0.0001734469,0.0000591427,0.0002068303,0.0004489556,0.998807,0.000008105661],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001051827,0.001137763,0.003566741,0.00645518,0.01278657,0.0001660443,0.001415989,0.00469066,0.9687293],"genre_scores_gemma":[0.002260466,0.0003867628,0.0007267719,0.0005320254,0.0005099413,0.00005179916,0.0007371494,0.001260906,0.9935341],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2267323,"threshold_uncertainty_score":0.3234061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005703164787302617,"score_gpt":0.2704836381333639,"score_spread":0.2647804733460613,"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."}}