{"id":"W2806882590","doi":"","title":"Unsupervised Multi-Lingual Cold Start Slot Filler Ensembling with the Knowledge Resolver System for TAC-KBP 2016.","year":2016,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Filler (materials); Resolver; Computer science; Artificial intelligence; Materials science; Composite material; Telecommunications","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":[0.004125545,0.002157532,0.001529346,0.00310576,0.002312357,0.003071968,0.003447418,0.002205904,0.01638526],"category_scores_gemma":[0.01617829,0.001133054,0.00127929,0.002474415,0.0009742912,0.00694793,0.004120615,0.003990042,0.02020282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001036956,"about_ca_system_score_gemma":0.003810394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01077854,"about_ca_topic_score_gemma":0.02318836,"domain_scores_codex":[0.9963111,0.001335389,0.0002722105,0.001351062,0.0004940715,0.0002360641],"domain_scores_gemma":[0.9934003,0.003222344,0.0001974215,0.001349356,0.001582932,0.0002476017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001376105,0.0006062953,0.00293939,0.00124612,0.0004277088,0.001008058,0.001603595,0.0180619,0.02357032,0.01203435,0.1942984,0.7428278],"study_design_scores_gemma":[0.0002958214,0.0003213001,0.003585512,0.0003714911,0.0003735587,0.0009225444,0.001770788,0.7878547,0.04582021,0.04887646,0.1095265,0.0002811727],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06955238,0.00298225,0.7548495,0.001343674,0.001891002,0.0005601767,0.02907874,0.1214953,0.01824685],"genre_scores_gemma":[0.2709867,0.0005274109,0.617972,0.0005202587,0.0003247449,0.0005362933,0.08758103,0.008242364,0.01330921],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01638526,"threshold_uncertainty_score":0.05481416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850573277556746,"score_gpt":0.2623846920669397,"score_spread":0.2438789592913722,"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."}}