{"id":"W6891731461","doi":"10.48448/pj77-dz40","title":"BAND: Biomedical Alert News Dataset | VIDEO","year":2024,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Inference; Social media; Event (particle physics); Benchmark (surveying); Disease surveillance; Scarcity; Named-entity recognition","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006032622,0.002238626,0.0008260203,0.004181585,0.0009148464,0.001558635,0.00176285,0.002435185,0.03495129],"category_scores_gemma":[0.00385116,0.0003479487,0.000869722,0.00398877,0.0004009008,0.001644157,0.001349029,0.001331539,0.03867179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00112302,"about_ca_system_score_gemma":0.001165405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02961265,"about_ca_topic_score_gemma":0.04612272,"domain_scores_codex":[0.9992537,0.0001179492,0.0001064371,0.0002197539,0.000202419,0.0000997203],"domain_scores_gemma":[0.9986855,0.0004258433,0.0001222038,0.0002594098,0.0003594318,0.0001476451],"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":[0.0002170279,0.00008937233,0.001407308,0.0007120856,0.00003481761,0.0001913953,0.00006616042,0.0005522438,0.001089646,0.000365856,0.9752333,0.02004077],"study_design_scores_gemma":[0.000232082,0.0001237979,0.01342206,0.0002928833,0.00006530909,0.0006138549,0.0004265496,0.008019025,0.003392644,0.001582291,0.9717544,0.00007508675],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003357141,0.0005854511,0.0006366831,0.000436512,0.0001892412,0.0001051865,0.9876899,0.002867607,0.004132381],"genre_scores_gemma":[0.002551326,0.0001516401,0.001160302,0.00008577917,0.00004365839,0.00008893148,0.9945512,0.00007251449,0.001294613],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03495129,"threshold_uncertainty_score":0.1169237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03026904471363482,"score_gpt":0.3370132114857833,"score_spread":0.3067441667721484,"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."}}