{"id":"W2805760825","doi":"","title":"CRIM’s Systems for the Tri-lingual Entity Detection and Linking Task.","year":2017,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Task (project management); Natural language processing; Engineering; Systems engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007194046,0.00005010158,0.00007671084,0.00002085566,0.0008453529,0.0002354288,0.0003678281,0.00002917798,2.376073e-7],"category_scores_gemma":[0.00006042138,0.00003687285,0.00001654028,0.00002571708,0.0001556812,0.0002054389,0.0001157994,0.00004451589,3.511388e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003941661,"about_ca_system_score_gemma":0.00001534907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005174564,"about_ca_topic_score_gemma":0.000008694726,"domain_scores_codex":[0.9995958,0.00002597508,0.0001126945,0.0001424638,0.00005299182,0.00007003595],"domain_scores_gemma":[0.999005,0.0002907805,0.0001222029,0.000496908,0.00006710739,0.00001802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000006123252,0.000004308107,0.00003933424,0.00003669816,0.000007336745,1.999073e-8,0.000472266,0.00003487616,0.0005307195,0.8638378,0.000001062431,0.1350295],"study_design_scores_gemma":[0.0002847611,0.00003626139,0.0008408292,0.00001883069,0.00004698895,0.00001055292,0.0008315275,0.03405197,0.009731512,0.9422486,0.01176307,0.0001350303],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03069459,0.001419463,0.9670421,0.0001223541,0.0001042259,0.0003091432,0.000002720272,0.00002671409,0.0002786285],"genre_scores_gemma":[0.9986095,0.0001114099,0.0008688694,0.00001055048,0.0001206341,0.0001570958,5.261813e-7,0.000002730924,0.0001187193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9679149,"threshold_uncertainty_score":0.6501856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02179054767458981,"score_gpt":0.2774205102755448,"score_spread":0.2556299626009549,"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."}}