{"id":"W2250730878","doi":"10.3115/v1/w15-0509","title":"From Argumentation Mining to Stance Classification","year":2015,"lang":"en","type":"article","venue":"","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Argument (complex analysis); Computer science; Argumentation theory; Artificial intelligence; Latent Dirichlet allocation; Classifier (UML); Topic model; Machine learning; Set (abstract data type); Natural language processing; Linguistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005799579,0.001481882,0.001521858,0.006566267,0.001370881,0.005691801,0.001993001,0.00265628,0.002437065],"category_scores_gemma":[0.02657837,0.000707493,0.001418429,0.005498748,0.001944549,0.008148167,0.003461561,0.003398697,0.001854873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00128646,"about_ca_system_score_gemma":0.00129489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000733193,"about_ca_topic_score_gemma":0.0007653678,"domain_scores_codex":[0.9931126,0.003502363,0.0005472114,0.001152752,0.001428121,0.0002569671],"domain_scores_gemma":[0.9816892,0.01316146,0.001399631,0.00150558,0.001767336,0.0004767329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002925037,0.0003849784,0.007249397,0.001003716,0.0002268004,0.0004061071,0.001117167,0.02175112,0.00505968,0.1390374,0.01844018,0.8050309],"study_design_scores_gemma":[0.00005428832,0.00007137746,0.002499419,0.0002842593,0.00006097696,0.0003437073,0.0004087513,0.3077752,0.004624104,0.6601362,0.02368408,0.00005761314],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02355701,0.006086349,0.9552552,0.005424362,0.0003523138,0.0001797719,0.0008279537,0.001109728,0.00720723],"genre_scores_gemma":[0.3324718,0.004244042,0.65413,0.0009715858,0.001362051,0.0003254754,0.002766661,0.0003538477,0.003374587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006566267,"threshold_uncertainty_score":0.03067148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09989513788844828,"score_gpt":0.3264486296949984,"score_spread":0.2265534918065501,"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."}}