{"id":"W7082288747","doi":"10.48448/1qe2-mg94","title":"Is External Information Useful for Stance Detection with LLMs?","year":2025,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Affect (linguistics); Contrast (vision); Macro; Work (physics); Motivated reasoning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001403215,0.0001402391,0.0001945933,0.0003177984,0.0001746315,0.00004977306,0.0001126339,0.00008038813,0.0001860829],"category_scores_gemma":[0.00006160684,0.000103869,0.00003971714,0.0003715694,0.0002547889,0.0001701431,0.00003631968,0.0001051121,0.00002928859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001379267,"about_ca_system_score_gemma":0.0003331522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001266976,"about_ca_topic_score_gemma":0.0002052584,"domain_scores_codex":[0.9989441,0.000002925766,0.000164483,0.0002198884,0.0004559665,0.0002126044],"domain_scores_gemma":[0.9992889,0.00002433607,0.000135466,0.000174765,0.0003080446,0.00006855721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001296797,0.0004066985,0.003093824,0.002477908,0.0002623204,0.00001458412,0.0002253297,0.00002118934,0.001061477,0.0114429,0.834021,0.145676],"study_design_scores_gemma":[0.00179548,0.000567227,0.001457527,0.001072204,0.00008634313,0.00001963927,0.0001736606,0.0009786767,0.001039069,0.001129321,0.9914739,0.0002069767],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005843104,0.001420884,0.4669459,0.0028216,0.001181868,0.002363233,0.0005681514,0.0003272972,0.5237868],"genre_scores_gemma":[0.0786447,0.001751935,0.1300714,0.01328204,0.002630377,0.0004212603,0.0003011728,0.0002477232,0.7726494],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3368745,"threshold_uncertainty_score":0.4235656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01658112368101316,"score_gpt":0.2924191999530936,"score_spread":0.2758380762720804,"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."}}