{"id":"W4403808708","doi":"10.48550/arxiv.2409.00222","title":"Can Large Language Models Address Open-Target Stance Detection?","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.004950017,0.002023046,0.001204605,0.00137032,0.0005918118,0.00270006,0.001756078,0.002068611,0.004213959],"category_scores_gemma":[0.02503917,0.0007395229,0.001253404,0.001111046,0.000647088,0.006851573,0.001622167,0.002857482,0.007504604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008562906,"about_ca_system_score_gemma":0.00137745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003477665,"about_ca_topic_score_gemma":0.006943993,"domain_scores_codex":[0.9973579,0.001531876,0.0001583223,0.0005575683,0.000248153,0.0001461087],"domain_scores_gemma":[0.9851165,0.0115809,0.000498046,0.001467729,0.0009829799,0.0003539166],"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":[0.001913079,0.0007831854,0.01800735,0.002038187,0.0007818775,0.0007206899,0.001534906,0.1815276,0.02748298,0.01584749,0.06681512,0.6825475],"study_design_scores_gemma":[0.0001387405,0.000181514,0.001172366,0.0001100079,0.0001037686,0.0002337617,0.0002881033,0.9504665,0.005165704,0.03096102,0.01113466,0.00004382612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1622587,0.00818636,0.7748052,0.007587408,0.00109342,0.0004706582,0.006942103,0.02690953,0.01174668],"genre_scores_gemma":[0.7394334,0.001716112,0.2391443,0.001612198,0.0006034413,0.0004562422,0.01053751,0.001914986,0.004581798],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004950017,"threshold_uncertainty_score":0.02617848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06989577715643526,"score_gpt":0.213450588198097,"score_spread":0.1435548110416618,"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."}}