{"id":"W2807172527","doi":"","title":"Event Argument Linking and Event Nugget Detection Task: IHMC DISCERN System Report.","year":2015,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Event (particle physics); Argument (complex analysis); Computer science; Task (project management); Real-time computing; Systems engineering; Engineering; Medicine; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.003258263,0.00204318,0.001982141,0.003487131,0.001810495,0.002710036,0.00276476,0.003423581,0.02743946],"category_scores_gemma":[0.02169625,0.0006894115,0.0009180252,0.002226333,0.0006614311,0.004174641,0.004023477,0.002941827,0.02402237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001610305,"about_ca_system_score_gemma":0.004230975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02855724,"about_ca_topic_score_gemma":0.04469571,"domain_scores_codex":[0.9981236,0.0003773962,0.0001535518,0.0006295328,0.0005280629,0.0001877714],"domain_scores_gemma":[0.9912485,0.004408658,0.000301165,0.001841106,0.001505418,0.0006951218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001931203,0.001177525,0.00728372,0.0009625716,0.0001865055,0.0004860228,0.0005112314,0.002264117,0.006697048,0.002695059,0.7822441,0.1935609],"study_design_scores_gemma":[0.0060537,0.001902257,0.05303157,0.0005445912,0.0009622636,0.002120764,0.003985787,0.2295327,0.08187655,0.03218189,0.5872809,0.000527115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3018501,0.004093652,0.06966957,0.008350719,0.002332542,0.006028752,0.4090421,0.1479285,0.05070399],"genre_scores_gemma":[0.2471532,0.0006148607,0.1586391,0.001324775,0.0006289305,0.002444012,0.5507618,0.00293189,0.03550148],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02855724,"threshold_uncertainty_score":0.09179407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01197976079154711,"score_gpt":0.2487218459279085,"score_spread":0.2367420851363614,"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."}}