{"id":"W2917934195","doi":"","title":"Cornell Belief and Sentiment System at TAC 2017.","year":2017,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Natural language processing; Artificial intelligence","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":[0.003121554,0.0008851379,0.000562969,0.002213628,0.001065867,0.001809535,0.001173106,0.001087571,0.0173652],"category_scores_gemma":[0.01148838,0.0003119091,0.000479913,0.001497067,0.0002887201,0.002908174,0.001253196,0.00163619,0.01358945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002291087,"about_ca_system_score_gemma":0.002035758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05834894,"about_ca_topic_score_gemma":0.1089298,"domain_scores_codex":[0.9987531,0.0003998223,0.00006280059,0.0002210768,0.0004236621,0.0001396802],"domain_scores_gemma":[0.996685,0.0008349355,0.0001094221,0.0005573487,0.00148271,0.0003305986],"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":[0.0005754592,0.0003766061,0.009656941,0.0001636591,0.00009153529,0.0001006929,0.0002652422,0.004746454,0.001169644,0.002645436,0.9093235,0.0708849],"study_design_scores_gemma":[0.0005030257,0.0003136164,0.03346991,0.0001496517,0.000194879,0.000118896,0.0006535607,0.4826651,0.009730711,0.0159712,0.4560348,0.0001945552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.2192199,0.001466749,0.05140059,0.007464609,0.002893482,0.001220614,0.5185431,0.0918974,0.1058936],"genre_scores_gemma":[0.3387349,0.0002768536,0.04816783,0.0006440562,0.0004574303,0.0007304583,0.5712165,0.002227521,0.03754453],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05834894,"threshold_uncertainty_score":0.1160187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01563454526654284,"score_gpt":0.2464192913199238,"score_spread":0.230784746053381,"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."}}