{"id":"W2425827634","doi":"","title":"The Conference Biomath 2016","year":2016,"lang":"en","type":"article","venue":"Biomath Communications","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bulgarian; Gratitude; Political science; Library science; Multidisciplinary approach; Social science; Sociology; Psychology; Computer science","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":[],"category_scores_codex":[0.004038588,0.002732756,0.001561422,0.003434606,0.002484696,0.01232606,0.002968889,0.00325931,0.3760183],"category_scores_gemma":[0.00630455,0.0005700187,0.001764983,0.001758676,0.0008150297,0.005619514,0.007691606,0.004057216,0.3246694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002289741,"about_ca_system_score_gemma":0.003931631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009943277,"about_ca_topic_score_gemma":0.001612548,"domain_scores_codex":[0.9969285,0.0006331458,0.0002193457,0.0005486729,0.001213986,0.0004563174],"domain_scores_gemma":[0.9962085,0.000331249,0.0002485608,0.0003304954,0.001247766,0.001633341],"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":[0.000183765,0.000064853,0.0001655107,0.0004190924,0.00001329688,0.00009109735,0.00005218495,0.0001723535,0.0007743585,0.003510972,0.9251995,0.06935302],"study_design_scores_gemma":[0.00001151437,0.00002442173,0.0001939913,0.0001323327,0.000003772251,0.00008662329,0.00003327046,0.00008645294,0.0001906662,0.00107784,0.9981517,0.000007290751],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.004923549,0.03836595,0.01695204,0.04667479,0.4251978,0.000864914,0.01456557,0.00773672,0.4447187],"genre_scores_gemma":[0.009912269,0.0174806,0.006750504,0.008520637,0.04536773,0.001274406,0.03200228,0.00362218,0.8750694],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3760183,"threshold_uncertainty_score":0.8900342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04526920426064305,"score_gpt":0.3217361331099121,"score_spread":0.276466928849269,"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."}}